NASA Astrophysics Data System (ADS)
Kokka, Alexander; Pulli, Tomi; Poikonen, Tuomas; Askola, Janne; Ikonen, Erkki
2017-08-01
This paper presents a fisheye camera method for determining spatial non-uniformity corrections in luminous flux measurements with integrating spheres. Using a fisheye camera installed into a port of an integrating sphere, the relative angular intensity distribution of the lamp under test is determined. This angular distribution is used for calculating the spatial non-uniformity correction for the lamp when combined with the spatial responsivity data of the sphere. The method was validated by comparing it to a traditional goniophotometric approach when determining spatial correction factors for 13 LED lamps with different angular spreads. The deviations between the spatial correction factors obtained using the two methods ranged from -0.15 % to 0.15%. The mean magnitude of the deviations was 0.06%. For a typical LED lamp, the expanded uncertainty (k = 2 ) for the spatial non-uniformity correction factor was evaluated to be 0.28%. The fisheye camera method removes the need for goniophotometric measurements in determining spatial non-uniformity corrections, thus resulting in considerable system simplification. Generally, no permanent modifications to existing integrating spheres are required.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Petrović, V. M.; Miladinović, T. B., E-mail: tanja.miladinovic@gmail.com
2016-05-15
Within the framework of the Ammosov–Delone–Krainov theory, we consider the angular and energy distribution of outgoing electrons due to ionization by a circularly polarized electromagnetic field. A correction of the ground ionization potential by the ponderomotive and Stark shift is incorporated in both distributions. Spatial dependence is analyzed.
NASA Astrophysics Data System (ADS)
Gao, Cheng-Yan; Wang, Guan-Yu; Zhang, Hao; Deng, Fu-Guo
2017-01-01
We present a self-error-correction spatial-polarization hyperentanglement distribution scheme for N-photon systems in a hyperentangled Greenberger-Horne-Zeilinger state over arbitrary collective-noise channels. In our scheme, the errors of spatial entanglement can be first averted by encoding the spatial-polarization hyperentanglement into the time-bin entanglement with identical polarization and defined spatial modes before it is transmitted over the fiber channels. After transmission over the noisy channels, the polarization errors introduced by the depolarizing noise can be corrected resorting to the time-bin entanglement. Finally, the parties in quantum communication can in principle share maximally hyperentangled states with a success probability of 100%.
NASA Astrophysics Data System (ADS)
Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish
2017-07-01
Use of General Circulation Model (GCM) precipitation and evapotranspiration sequences for hydrologic modelling can result in unrealistic simulations due to the coarse scales at which GCMs operate and the systematic biases they contain. The Bias Correction Spatial Disaggregation (BCSD) method is a popular statistical downscaling and bias correction method developed to address this issue. The advantage of BCSD is its ability to reduce biases in the distribution of precipitation totals at the GCM scale and then introduce more realistic variability at finer scales than simpler spatial interpolation schemes. Although BCSD corrects biases at the GCM scale before disaggregation; at finer spatial scales biases are re-introduced by the assumptions made in the spatial disaggregation process. Our study focuses on this limitation of BCSD and proposes a rank-based approach that aims to reduce the spatial disaggregation bias especially for both low and high precipitation extremes. BCSD requires the specification of a multiplicative bias correction anomaly field that represents the ratio of the fine scale precipitation to the disaggregated precipitation. It is shown that there is significant temporal variation in the anomalies, which is masked when a mean anomaly field is used. This can be improved by modelling the anomalies in rank-space. Results from the application of the rank-BCSD procedure improve the match between the distributions of observed and downscaled precipitation at the fine scale compared to the original BCSD approach. Further improvements in the distribution are identified when a scaling correction to preserve mass in the disaggregation process is implemented. An assessment of the approach using a single GCM over Australia shows clear advantages especially in the simulation of particularly low and high downscaled precipitation amounts.
Scene-based nonuniformity correction using local constant statistics.
Zhang, Chao; Zhao, Wenyi
2008-06-01
In scene-based nonuniformity correction, the statistical approach assumes all possible values of the true-scene pixel are seen at each pixel location. This global-constant-statistics assumption does not distinguish fixed pattern noise from spatial variations in the average image. This often causes the "ghosting" artifacts in the corrected images since the existing spatial variations are treated as noises. We introduce a new statistical method to reduce the ghosting artifacts. Our method proposes a local-constant statistics that assumes that the temporal signal distribution is not constant at each pixel but is locally true. This considers statistically a constant distribution in a local region around each pixel but uneven distribution in a larger scale. Under the assumption that the fixed pattern noise concentrates in a higher spatial-frequency domain than the distribution variation, we apply a wavelet method to the gain and offset image of the noise and separate out the pattern noise from the spatial variations in the temporal distribution of the scene. We compare the results to the global-constant-statistics method using a clean sequence with large artificial pattern noises. We also apply the method to a challenging CCD video sequence and a LWIR sequence to show how effective it is in reducing noise and the ghosting artifacts.
NASA Astrophysics Data System (ADS)
Talamo, Alberto; Gohar, Y.; Cao, Y.; Zhong, Z.; Kiyavitskaya, H.; Bournos, V.; Fokov, Y.; Routkovskaya, C.
2012-03-01
In subcritical assemblies, the Bell and Glasstone spatial correction factor is used to correct the measured reactivity from different detector positions. In addition to the measuring position, several other parameters affect the correction factor: the detector material, the detector size, and the energy-angle distribution of source neutrons. The effective multiplication factor calculated by computer codes in criticality mode slightly differs from the average value obtained from the measurements in the different experimental channels of the subcritical assembly, which are corrected by the Bell and Glasstone spatial correction factor. Generally, this difference is due to (1) neutron counting errors; (2) geometrical imperfections, which are not simulated in the calculational model, and (3) quantities and distributions of material impurities, which are missing from the material definitions. This work examines these issues and it focuses on the detector choice and the calculation methodologies. The work investigated the YALINA Booster subcritical assembly of Belarus, which has been operated with three different fuel enrichments in the fast zone either: high (90%) and medium (36%), medium (36%), or low (21%) enriched uranium fuel.
Nonuniformity correction of imaging systems with a spatially nonhomogeneous radiation source.
Gutschwager, Berndt; Hollandt, Jörg
2015-12-20
We present a novel method of nonuniformity correction of imaging systems in a wide optical spectral range by applying a radiation source with an unknown and spatially nonhomogeneous radiance or radiance temperature distribution. The benefit of this method is that it can be applied with radiation sources of arbitrary spatial radiance or radiance temperature distribution and only requires the sufficient temporal stability of this distribution during the measurement process. The method is based on the recording of several (at least three) images of a radiation source and a purposeful row- and line-shift of these sequent images in relation to the first primary image. The mathematical procedure is explained in detail. Its numerical verification with a source of a predefined nonhomogenous radiance distribution and a thermal imager of a predefined nonuniform focal plane array responsivity is presented.
NASA Technical Reports Server (NTRS)
Jefferies, S. M.; Duvall, T. L., Jr.
1991-01-01
A measurement of the intensity distribution in an image of the solar disk will be corrupted by a spatial redistribution of the light that is caused by the earth's atmosphere and the observing instrument. A simple correction method is introduced here that is applicable for solar p-mode intensity observations obtained over a period of time in which there is a significant change in the scattering component of the point spread function. The method circumvents the problems incurred with an accurate determination of the spatial point spread function and its subsequent deconvolution from the observations. The method only corrects the spherical harmonic coefficients that represent the spatial frequencies present in the image and does not correct the image itself.
NASA Astrophysics Data System (ADS)
Gutschwager, Berndt; Hollandt, Jörg
2017-01-01
We present a novel method of nonuniformity correction (NUC) of infrared cameras and focal plane arrays (FPA) in a wide optical spectral range by reading radiance temperatures and by applying a radiation source with an unknown and spatially nonhomogeneous radiance temperature distribution. The benefit of this novel method is that it works with the display and the calculation of radiance temperatures, it can be applied to radiation sources of arbitrary spatial radiance temperature distribution, and it only requires sufficient temporal stability of this distribution during the measurement process. In contrast to this method, an initially presented method described the calculation of NUC correction with the reading of monitored radiance values. Both methods are based on the recording of several (at least three) images of a radiation source and a purposeful row- and line-shift of these sequent images in relation to the first primary image. The mathematical procedure is explained in detail. Its numerical verification with a source of a predefined nonhomogeneous radiance temperature distribution and a thermal imager of a predefined nonuniform FPA responsivity is presented.
A simple enrichment correction factor for improving erosion estimation by rare earth oxide tracers
USDA-ARS?s Scientific Manuscript database
Spatially distributed soil erosion data are needed to better understanding soil erosion processes and validating distributed erosion models. Rare earth element (REE) oxides were used to generate spatial erosion data. However, a general concern on the accuracy of the technique arose due to selective ...
NASA Astrophysics Data System (ADS)
Nahar, Jannatun; Johnson, Fiona; Sharma, Ashish
2018-02-01
Conventional bias correction is usually applied on a grid-by-grid basis, meaning that the resulting corrections cannot address biases in the spatial distribution of climate variables. To solve this problem, a two-step bias correction method is proposed here to correct time series at multiple locations conjointly. The first step transforms the data to a set of statistically independent univariate time series, using a technique known as independent component analysis (ICA). The mutually independent signals can then be bias corrected as univariate time series and back-transformed to improve the representation of spatial dependence in the data. The spatially corrected data are then bias corrected at the grid scale in the second step. The method has been applied to two CMIP5 General Circulation Model simulations for six different climate regions of Australia for two climate variables—temperature and precipitation. The results demonstrate that the ICA-based technique leads to considerable improvements in temperature simulations with more modest improvements in precipitation. Overall, the method results in current climate simulations that have greater equivalency in space and time with observational data.
Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun
2014-01-01
Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation.
Dong, Yingying; Luo, Ruisen; Feng, Haikuan; Wang, Jihua; Zhao, Jinling; Zhu, Yining; Yang, Guijun
2014-01-01
Differences exist among analysis results of agriculture monitoring and crop production based on remote sensing observations, which are obtained at different spatial scales from multiple remote sensors in same time period, and processed by same algorithms, models or methods. These differences can be mainly quantitatively described from three aspects, i.e. multiple remote sensing observations, crop parameters estimation models, and spatial scale effects of surface parameters. Our research proposed a new method to analyse and correct the differences between multi-source and multi-scale spatial remote sensing surface reflectance datasets, aiming to provide references for further studies in agricultural application with multiple remotely sensed observations from different sources. The new method was constructed on the basis of physical and mathematical properties of multi-source and multi-scale reflectance datasets. Theories of statistics were involved to extract statistical characteristics of multiple surface reflectance datasets, and further quantitatively analyse spatial variations of these characteristics at multiple spatial scales. Then, taking the surface reflectance at small spatial scale as the baseline data, theories of Gaussian distribution were selected for multiple surface reflectance datasets correction based on the above obtained physical characteristics and mathematical distribution properties, and their spatial variations. This proposed method was verified by two sets of multiple satellite images, which were obtained in two experimental fields located in Inner Mongolia and Beijing, China with different degrees of homogeneity of underlying surfaces. Experimental results indicate that differences of surface reflectance datasets at multiple spatial scales could be effectively corrected over non-homogeneous underlying surfaces, which provide database for further multi-source and multi-scale crop growth monitoring and yield prediction, and their corresponding consistency analysis evaluation. PMID:25405760
NASA Astrophysics Data System (ADS)
Fedyushin, B. T.
1992-01-01
The concepts developed earlier are used to propose a simple analytic model describing the spatial-temporal distribution of a mechanical load (pressure, impulse) resulting from interaction of laser radiation with a planar barrier surrounded by air. The correctness of the model is supported by a comparison with experimental results.
Khachatryan, Vardan
2015-04-24
Our search is presented for quark contact interactions and extra spatial dimensions in proton–proton collisions at √s=8TeVusing dijet angular distributions. The search is based on a data set corresponding to an integrated luminosity of 19.7fb -1collected by the CMS detector at the CERN LHC. Dijet angular distributions are found to be in agreement with the perturbative QCD predictions that include electroweak corrections. Limits on the contact interaction scale from a variety of models at next-to-leading order in QCD corrections are obtained. A benchmark model in which only left-handed quarks participate is excluded up to a scale of 9.0 (11.7)TeV formore » destructive (constructive) interference at 95% confidence level. Finally, lower limits between 5.9 and 8.4TeV on the scale of virtual graviton exchange are extracted for the Arkani-Hamed–Dimopoulos–Dvali model of extra spatial dimensions.« less
NASA Astrophysics Data System (ADS)
Khachatryan, V.; Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Bergauer, T.; Dragicevic, M.; Erö, J.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; Kiesenhofer, W.; Knünz, V.; Krammer, M.; Krätschmer, I.; Liko, D.; Mikulec, I.; Rabady, D.; Rahbaran, B.; Rohringer, H.; Schöfbeck, R.; Strauss, J.; Treberer-Treberspurg, W.; Waltenberger, W.; Wulz, C.-E.; Mossolov, V.; Shumeiko, N.; Suarez Gonzalez, J.; Alderweireldt, S.; Bansal, M.; Bansal, S.; Cornelis, T.; De Wolf, E. A.; Janssen, X.; Knutsson, A.; Lauwers, J.; Luyckx, S.; Ochesanu, S.; Rougny, R.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Blekman, F.; Blyweert, S.; D'Hondt, J.; Daci, N.; Heracleous, N.; Keaveney, J.; Lowette, S.; Maes, M.; Olbrechts, A.; Python, Q.; Strom, D.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Onsem, G. P.; Villella, I.; Caillol, C.; Clerbaux, B.; De Lentdecker, G.; Dobur, D.; Favart, L.; Gay, A. P. R.; Grebenyuk, A.; Léonard, A.; Mohammadi, A.; Perniè, L.; Reis, T.; Seva, T.; Thomas, L.; Vander Velde, C.; Vanlaer, P.; Wang, J.; Zenoni, F.; Adler, V.; Beernaert, K.; Benucci, L.; Cimmino, A.; Costantini, S.; Crucy, S.; Dildick, S.; Fagot, A.; Garcia, G.; Mccartin, J.; Ocampo Rios, A. A.; Ryckbosch, D.; Salva Diblen, S.; Sigamani, M.; Strobbe, N.; Thyssen, F.; Tytgat, M.; Yazgan, E.; Zaganidis, N.; Basegmez, S.; Beluffi, C.; Bruno, G.; Castello, R.; Caudron, A.; Ceard, L.; Da Silveira, G. G.; Delaere, C.; du Pree, T.; Favart, D.; Forthomme, L.; Giammanco, A.; Hollar, J.; Jafari, A.; Jez, P.; Komm, M.; Lemaitre, V.; Nuttens, C.; Pagano, D.; Perrini, L.; Pin, A.; Piotrzkowski, K.; Popov, A.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Vizan Garcia, J. M.; Beliy, N.; Caebergs, T.; Daubie, E.; Hammad, G. H.; Aldá Júnior, W. L.; Alves, G. A.; Brito, L.; Correa Martins Junior, M.; Dos Reis Martins, T.; Mora Herrera, C.; Pol, M. E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Malbouisson, H.; Matos Figueiredo, D.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santaolalla, J.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Vilela Pereira, A.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Novaes, S. F.; Padula, Sandra S.; Aleksandrov, A.; Genchev, V.; Iaydjiev, P.; Marinov, A.; Piperov, S.; Rodozov, M.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Hadjiiska, R.; Kozhuharov, V.; Litov, L.; Pavlov, B.; Petkov, P.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Cheng, T.; Du, R.; Jiang, C. H.; Plestina, R.; Romeo, F.; Tao, J.; Wang, Z.; Asawatangtrakuldee, C.; Ban, Y.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Zou, W.; Avila, C.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; Gomez Moreno, B.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Polic, D.; Puljak, I.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Kadija, K.; Luetic, J.; Mekterovic, D.; Sudic, L.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Bodlak, M.; Finger, M.; Finger, M.; Assran, Y.; Elgammal, S.; Mahmoud, M. A.; Radi, A.; Kadastik, M.; Murumaa, M.; Raidal, M.; Tiko, A.; Eerola, P.; Fedi, G.; Voutilainen, M.; Härkönen, J.; Karimäki, V.; Kinnunen, R.; Kortelainen, M. J.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Mäenpää, T.; Peltola, T.; Tuominen, E.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Locci, E.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Baffioni, S.; Beaudette, F.; Busson, P.; Charlot, C.; Dahms, T.; Dalchenko, M.; Dobrzynski, L.; Filipovic, N.; Florent, A.; Granier de Cassagnac, R.; Mastrolorenzo, L.; Miné, P.; Mironov, C.; Naranjo, I. N.; Nguyen, M.; Ochando, C.; Paganini, P.; Regnard, S.; Salerno, R.; Sauvan, J. B.; Sirois, Y.; Veelken, C.; Yilmaz, Y.; Zabi, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Chabert, E. C.; Collard, C.; Conte, E.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Goetzmann, C.; Le Bihan, A.-C.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Beaupere, N.; Boudoul, G.; Bouvier, E.; Brochet, S.; Carrillo Montoya, C. A.; Chasserat, J.; Chierici, R.; Contardo, D.; Depasse, P.; El Mamouni, H.; Fan, J.; Fay, J.; Gascon, S.; Gouzevitch, M.; Ille, B.; Kurca, T.; Lethuillier, M.; Mirabito, L.; Perries, S.; Ruiz Alvarez, J. D.; Sabes, D.; Sgandurra, L.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Xiao, H.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Bontenackels, M.; Edelhoff, M.; Feld, L.; Heister, A.; Hindrichs, O.; Klein, K.; Ostapchuk, A.; Raupach, F.; Sammet, J.; Schael, S.; Weber, H.; Wittmer, B.; Zhukov, V.; Ata, M.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Erdmann, M.; Fischer, R.; Güth, A.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Klingebiel, D.; Knutzen, S.; Kreuzer, P.; Merschmeyer, M.; Meyer, A.; Millet, P.; Olschewski, M.; Padeken, K.; Papacz, P.; Reithler, H.; Schmitz, S. A.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Weber, M.; Cherepanov, V.; Erdogan, Y.; Flügge, G.; Geenen, H.; Geisler, M.; Haj Ahmad, W.; Hoehle, F.; Kargoll, B.; Kress, T.; Kuessel, Y.; Künsken, A.; Lingemann, J.; Nowack, A.; Nugent, I. M.; Perchalla, L.; Pooth, O.; Stahl, A.; Asin, I.; Bartosik, N.; Behr, J.; Behrenhoff, W.; Behrens, U.; Bell, A. J.; Bergholz, M.; Bethani, A.; Borras, K.; Burgmeier, A.; Cakir, A.; Calligaris, L.; Campbell, A.; Choudhury, S.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Dooling, S.; Dorland, T.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Flucke, G.; Garay Garcia, J.; Geiser, A.; Gunnellini, P.; Hauk, J.; Hempel, M.; Horton, D.; Jung, H.; Kalogeropoulos, A.; Kasemann, M.; Katsas, P.; Kieseler, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; Lutz, B.; Mankel, R.; Marfin, I.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Naumann-Emme, S.; Nayak, A.; Novgorodova, O.; Ntomari, E.; Perrey, H.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Ribeiro Cipriano, P. M.; Roland, B.; Ron, E.; Sahin, M. Ö.; Salfeld-Nebgen, J.; Saxena, P.; Schmidt, R.; Schoerner-Sadenius, T.; Schröder, M.; Seitz, C.; Spannagel, S.; Vargas Trevino, A. D. R.; Walsh, R.; Wissing, C.; Aldaya Martin, M.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Erfle, J.; Garutti, E.; Goebel, K.; Görner, M.; Haller, J.; Hoffmann, M.; Höing, R. S.; Kirschenmann, H.; Klanner, R.; Kogler, R.; Lange, J.; Lapsien, T.; Lenz, T.; Marchesini, I.; Ott, J.; Peiffer, T.; Perieanu, A.; Pietsch, N.; Poehlsen, J.; Poehlsen, T.; Rathjens, D.; Sander, C.; Schettler, H.; Schleper, P.; Schlieckau, E.; Schmidt, A.; Seidel, M.; Sola, V.; Stadie, H.; Steinbrück, G.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Barth, C.; Baus, C.; Berger, J.; Böser, C.; Butz, E.; Chwalek, T.; De Boer, W.; Descroix, A.; Dierlamm, A.; Feindt, M.; Frensch, F.; Giffels, M.; Gilbert, A.; Hartmann, F.; Hauth, T.; Husemann, U.; Katkov, I.; Kornmayer, A.; Kuznetsova, E.; Lobelle Pardo, P.; Mozer, M. U.; Müller, Th.; Nürnberg, A.; Quast, G.; Rabbertz, K.; Ratnikov, F.; Röcker, S.; Simonis, H. J.; Stober, F. M.; Ulrich, R.; Wagner-Kuhr, J.; Wayand, S.; Weiler, T.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Markou, A.; Markou, C.; Psallidas, A.; Topsis-Giotis, I.; Agapitos, A.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Stiliaris, E.; Aslanoglou, X.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Strologas, J.; Bencze, G.; Hajdu, C.; Hidas, P.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Molnar, J.; Palinkas, J.; Szillasi, Z.; Makovec, A.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Swain, S. K.; Beri, S. B.; Bhatnagar, V.; Gupta, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, M.; Kumar, R.; Mittal, M.; Nishu, N.; Singh, J. B.; Kumar, Ashok; Kumar, Arun; Ahuja, S.; Bhardwaj, A.; Choudhary, B. C.; Kumar, A.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, V.; Banerjee, S.; Bhattacharya, S.; Chatterjee, K.; Dutta, S.; Gomber, B.; Jain, Sa.; Jain, Sh.; Khurana, R.; Modak, A.; Mukherjee, S.; Roy, D.; Sarkar, S.; Sharan, M.; Abdulsalam, A.; Dutta, D.; Kailas, S.; Kumar, V.; Mohanty, A. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Banerjee, S.; Bhowmik, S.; Chatterjee, R. M.; Dewanjee, R. K.; Dugad, S.; Ganguly, S.; Ghosh, S.; Guchait, M.; Gurtu, A.; Kole, G.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Mohanty, G. B.; Parida, B.; Sudhakar, K.; Wickramage, N.; Bakhshiansohi, H.; Behnamian, H.; Etesami, S. M.; Fahim, A.; Goldouzian, R.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Chhibra, S. S.; Colaleo, A.; Creanza, D.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Abbiendi, G.; Benvenuti, A. C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Primavera, F.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Travaglini, R.; Albergo, S.; Cappello, G.; Chiorboli, M.; Costa, S.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Gallo, E.; Gonzi, S.; Gori, V.; Lenzi, P.; Meschini, M.; Paoletti, S.; Sguazzoni, G.; Tropiano, A.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Ferretti, R.; Ferro, F.; Lo Vetere, M.; Robutti, E.; Tosi, S.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Gerosa, R.; Ghezzi, A.; Govoni, P.; Lucchini, M. T.; Malvezzi, S.; Manzoni, R. A.; Martelli, A.; Marzocchi, B.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Ragazzi, S.; Redaelli, N.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; Di Guida, S.; Fabozzi, F.; Iorio, A. O. M.; Lista, L.; Meola, S.; Merola, M.; Paolucci, P.; Azzi, P.; Bacchetta, N.; Bisello, D.; Branca, A.; Carlin, R.; Checchia, P.; Dall'Osso, M.; Dorigo, T.; Dosselli, U.; Galanti, M.; Gasparini, F.; Gasparini, U.; Giubilato, P.; Gozzelino, A.; Kanishchev, K.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Tosi, M.; Zotto, P.; Zucchetta, A.; Zumerle, G.; Gabusi, M.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vitulo, P.; Biasini, M.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Spiezia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Broccolo, G.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Donato, S.; Fiori, F.; Foà, L.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Moon, C. S.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Serban, A. T.; Spagnolo, P.; Squillacioti, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Vernieri, C.; Barone, L.; Cavallari, F.; D'imperio, G.; Del Re, D.; Diemoz, M.; Jorda, C.; Longo, E.; Margaroli, F.; Meridiani, P.; Micheli, F.; Nourbakhsh, S.; Organtini, G.; Paramatti, R.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Soffi, L.; Traczyk, P.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bellan, R.; Biino, C.; Cartiglia, N.; Casasso, S.; Costa, M.; Degano, A.; Demaria, N.; Finco, L.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Musich, M.; Obertino, M. M.; Ortona, G.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Potenza, A.; Romero, A.; Ruspa, M.; Sacchi, R.; Solano, A.; Staiano, A.; Tamponi, U.; Belforte, S.; Candelise, V.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Gobbo, B.; La Licata, C.; Marone, M.; Schizzi, A.; Umer, T.; Zanetti, A.; Chang, S.; Kropivnitskaya, A.; Nam, S. K.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Kong, D. J.; Lee, S.; Oh, Y. D.; Park, H.; Sakharov, A.; Son, D. C.; Kim, T. J.; Kim, J. Y.; Song, S.; Choi, S.; Gyun, D.; Hong, B.; Jo, M.; Kim, H.; Kim, Y.; Lee, B.; Lee, K. S.; Park, S. K.; Roh, Y.; Choi, M.; Kim, J. H.; Park, I. C.; Ryu, G.; Ryu, M. S.; Choi, Y.; Choi, Y. K.; Goh, J.; Kim, D.; Kwon, E.; Lee, J.; Seo, H.; Yu, I.; Juodagalvis, A.; Komaragiri, J. R.; Md Ali, M. A. B.; Casimiro Linares, E.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-de La Cruz, I.; Hernandez-Almada, A.; Lopez-Fernandez, R.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Vazquez Valencia, F.; Pedraza, I.; Salazar Ibarguen, H. A.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Reucroft, S.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khan, W. A.; Khurshid, T.; Shoaib, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Zalewski, P.; Brona, G.; Bunkowski, K.; Cwiok, M.; Dominik, W.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Wolszczak, W.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Faccioli, P.; Ferreira Parracho, P. G.; Gallinaro, M.; Lloret Iglesias, L.; Nguyen, F.; Rodrigues Antunes, J.; Seixas, J.; Varela, J.; Vischia, P.; Bunin, P.; Gavrilenko, M.; Golutvin, I.; Gorbunov, I.; Karjavin, V.; Konoplyanikov, V.; Lanev, A.; Malakhov, A.; Matveev, V.; Moisenz, P.; Palichik, V.; Perelygin, V.; Savina, M.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Zarubin, A.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Levchenko, P.; Murzin, V.; Oreshkin, V.; Smirnov, I.; Sulimov, V.; Uvarov, L.; Vavilov, S.; Vorobyev, A.; Vorobyev, An.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Pozdnyakov, I.; Safronov, G.; Semenov, S.; Spiridonov, A.; Stolin, V.; Vlasov, E.; Zhokin, A.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Leonidov, A.; Mesyats, G.; Rusakov, S. V.; Vinogradov, A.; Belyaev, A.; Boos, E.; Bunichev, V.; Dubinin, M.; Dudko, L.; Ershov, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Obraztsov, S.; Perfilov, M.; Petrushanko, S.; Savrin, V.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Tourtchanovitch, L.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Ekmedzic, M.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; Battilana, C.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Domínguez Vázquez, D.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; Albajar, C.; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Brun, H.; Cuevas, J.; Fernandez Menendez, J.; Folgueras, S.; Gonzalez Caballero, I.; Brochero Cifuentes, J. A.; Cabrillo, I. J.; Calderon, A.; Duarte Campderros, J.; Fernandez, M.; Gomez, G.; Graziano, A.; Lopez Virto, A.; Marco, J.; Marco, R.; Martinez Rivero, C.; Matorras, F.; Munoz Sanchez, F. J.; Piedra Gomez, J.; Rodrigo, T.; Rodríguez-Marrero, A. Y.; Ruiz-Jimeno, A.; Scodellaro, L.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Auzinger, G.; Bachtis, M.; Baillon, P.; Ball, A. H.; Barney, D.; Benaglia, A.; Bendavid, J.; Benhabib, L.; Benitez, J. F.; Bernet, C.; Bloch, P.; Bocci, A.; Bonato, A.; Bondu, O.; Botta, C.; Breuker, H.; Camporesi, T.; Cerminara, G.; Colafranceschi, S.; D'Alfonso, M.; d'Enterria, D.; Dabrowski, A.; David, A.; De Guio, F.; De Roeck, A.; De Visscher, S.; Di Marco, E.; Dobson, M.; Dordevic, M.; Dorney, B.; Dupont-Sagorin, N.; Elliott-Peisert, A.; Eugster, J.; Franzoni, G.; Funk, W.; Gigi, D.; Gill, K.; Giordano, D.; Girone, M.; Glege, F.; Guida, R.; Gundacker, S.; Guthoff, M.; Hammer, J.; Hansen, M.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Kousouris, K.; Krajczar, K.; Lecoq, P.; Lourenço, C.; Magini, N.; Malgeri, L.; Mannelli, M.; Marrouche, J.; Masetti, L.; Meijers, F.; Mersi, S.; Meschi, E.; Moortgat, F.; Morovic, S.; Mulders, M.; Musella, P.; Orsini, L.; Pape, L.; Perez, E.; Perrozzi, L.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Pimiä, M.; Piparo, D.; Plagge, M.; Racz, A.; Rolandi, G.; Rovere, M.; Sakulin, H.; Schäfer, C.; Schwick, C.; Sharma, A.; Siegrist, P.; Silva, P.; Simon, M.; Sphicas, P.; Spiga, D.; Steggemann, J.; Stieger, B.; Stoye, M.; Takahashi, Y.; Treille, D.; Tsirou, A.; Veres, G. I.; Wardle, N.; Wöhri, H. K.; Wollny, H.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Renker, D.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Buchmann, M. A.; Casal, B.; Chanon, N.; Dissertori, G.; Dittmar, M.; Donegà, M.; Dünser, M.; Eller, P.; Grab, C.; Hits, D.; Hoss, J.; Lustermann, W.; Mangano, B.; Marini, A. C.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meister, D.; Mohr, N.; Nägeli, C.; Nessi-Tedaldi, F.; Pandolfi, F.; Pauss, F.; Peruzzi, M.; Quittnat, M.; Rebane, L.; Rossini, M.; Starodumov, A.; Takahashi, M.; Theofilatos, K.; Wallny, R.; Weber, H. A.; Amsler, C.; Canelli, M. F.; Chiochia, V.; De Cosa, A.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Lange, C.; Millan Mejias, B.; Ngadiuba, J.; Robmann, P.; Ronga, F. J.; Taroni, S.; Verzetti, M.; Yang, Y.; Cardaci, M.; Chen, K. H.; Ferro, C.; Kuo, C. M.; Lin, W.; Lu, Y. J.; Volpe, R.; Yu, S. S.; Chang, P.; Chang, Y. H.; Chang, Y. W.; Chao, Y.; Chen, K. F.; Chen, P. H.; Dietz, C.; Grundler, U.; Hou, W.-S.; Kao, K. Y.; Lei, Y. J.; Liu, Y. F.; Lu, R.-S.; Majumder, D.; Petrakou, E.; Tzeng, Y. M.; Wilken, R.; Asavapibhop, B.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Bakirci, M. N.; Cerci, S.; Dozen, C.; Dumanoglu, I.; Eskut, E.; Girgis, S.; Gokbulut, G.; Gurpinar, E.; Hos, I.; Kangal, E. E.; Kayis Topaksu, A.; Onengut, G.; Ozdemir, K.; Ozturk, S.; Polatoz, A.; Sunar Cerci, D.; Tali, B.; Topakli, H.; Vergili, M.; Akin, I. V.; Bilin, B.; Bilmis, S.; Gamsizkan, H.; Isildak, B.; Karapinar, G.; Ocalan, K.; Sekmen, S.; Surat, U. E.; Yalvac, M.; Zeyrek, M.; Albayrak, E. A.; Gülmez, E.; Kaya, M.; Kaya, O.; Yetkin, T.; Cankocak, K.; Vardarlı, F. I.; Levchuk, L.; Sorokin, P.; Brooke, J. J.; Clement, E.; Cussans, D.; Flacher, H.; Goldstein, J.; Grimes, M.; Heath, G. P.; Heath, H. F.; Jacob, J.; Kreczko, L.; Lucas, C.; Meng, Z.; Newbold, D. M.; Paramesvaran, S.; Poll, A.; Sakuma, T.; Senkin, S.; Smith, V. J.; Williams, T.; Bell, K. W.; Belyaev, A.; Brew, C.; Brown, R. M.; Cockerill, D. J. A.; Coughlan, J. A.; Harder, K.; Harper, S.; Olaiya, E.; Petyt, D.; Shepherd-Themistocleous, C. H.; Thea, A.; Tomalin, I. R.; Womersley, W. J.; Worm, S. D.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Burton, D.; Colling, D.; Cripps, N.; Cutajar, M.; Dauncey, P.; Davies, G.; Della Negra, M.; Dunne, P.; Ferguson, W.; Fulcher, J.; Futyan, D.; Hall, G.; Iles, G.; Jarvis, M.; Karapostoli, G.; Kenzie, M.; Lane, R.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mathias, B.; Nash, J.; Nikitenko, A.; Pela, J.; Pesaresi, M.; Petridis, K.; Raymond, D. M.; Rogerson, S.; Rose, A.; Seez, C.; Sharp, P.; Tapper, A.; Vazquez Acosta, M.; Virdee, T.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Leggat, D.; Leslie, D.; Martin, W.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Dittmann, J.; Hatakeyama, K.; Kasmi, A.; Liu, H.; Scarborough, T.; Charaf, O.; Cooper, S. I.; Henderson, C.; Rumerio, P.; Avetisyan, A.; Bose, T.; Fantasia, C.; Lawson, P.; Richardson, C.; Rohlf, J.; St. John, J.; Sulak, L.; Alimena, J.; Berry, E.; Bhattacharya, S.; Christopher, G.; Cutts, D.; Demiragli, Z.; Dhingra, N.; Ferapontov, A.; Garabedian, A.; Heintz, U.; Kukartsev, G.; Laird, E.; Landsberg, G.; Luk, M.; Narain, M.; Segala, M.; Sinthuprasith, T.; Speer, T.; Swanson, J.; Breedon, R.; Breto, G.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Gardner, M.; Ko, W.; Lander, R.; Miceli, T.; Mulhearn, M.; Pellett, D.; Pilot, J.; Ricci-Tam, F.; Searle, M.; Shalhout, S.; Smith, J.; Squires, M.; Stolp, D.; Tripathi, M.; Wilbur, S.; Yohay, R.; Cousins, R.; Everaerts, P.; Farrell, C.; Hauser, J.; Ignatenko, M.; Rakness, G.; Takasugi, E.; Valuev, V.; Weber, M.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Hanson, G.; Heilman, J.; Ivova Rikova, M.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Luthra, A.; Malberti, M.; Olmedo Negrete, M.; Shrinivas, A.; Sumowidagdo, S.; Wimpenny, S.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; D'Agnolo, R. T.; Holzner, A.; Kelley, R.; Klein, D.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Palmer, C.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Sudano, E.; Tadel, M.; Tu, Y.; Vartak, A.; Welke, C.; Würthwein, F.; Yagil, A.; Barge, D.; Bradmiller-Feld, J.; Campagnari, C.; Danielson, T.; Dishaw, A.; Dutta, V.; Flowers, K.; Franco Sevilla, M.; Geffert, P.; George, C.; Golf, F.; Gouskos, L.; Incandela, J.; Justus, C.; Mccoll, N.; Richman, J.; Stuart, D.; To, W.; West, C.; Yoo, J.; Apresyan, A.; Bornheim, A.; Bunn, J.; Chen, Y.; Duarte, J.; Mott, A.; Newman, H. B.; Pena, C.; Rogan, C.; Spiropulu, M.; Timciuc, V.; Vlimant, J. R.; Wilkinson, R.; Xie, S.; Zhu, R. Y.; Azzolini, V.; Calamba, A.; Carlson, B.; Ferguson, T.; Iiyama, Y.; Paulini, M.; Russ, J.; Vogel, H.; Vorobiev, I.; Cumalat, J. P.; Ford, W. T.; Gaz, A.; Krohn, M.; Luiggi Lopez, E.; Nauenberg, U.; Smith, J. G.; Stenson, K.; Ulmer, K. A.; Wagner, S. R.; Alexander, J.; Chatterjee, A.; Chaves, J.; Chu, J.; Dittmer, S.; Eggert, N.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Ryd, A.; Salvati, E.; Skinnari, L.; Sun, W.; Teo, W. D.; Thom, J.; Thompson, J.; Tucker, J.; Weng, Y.; Winstrom, L.; Wittich, P.; Winn, D.; Abdullin, S.; Albrow, M.; Anderson, J.; Apollinari, G.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gao, Y.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hanlon, J.; Hare, D.; Harris, R. M.; Hirschauer, J.; Hooberman, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Kaadze, K.; Klima, B.; Kreis, B.; Kwan, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, T.; Lykken, J.; Maeshima, K.; Marraffino, J. M.; Martinez Outschoorn, V. I.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mishra, K.; Mrenna, S.; Musienko, Y.; Nahn, S.; Newman-Holmes, C.; O'Dell, V.; Prokofyev, O.; Sexton-Kennedy, E.; Sharma, S.; Soha, A.; Spalding, W. J.; Spiegel, L.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vidal, R.; Whitbeck, A.; Whitmore, J.; Yang, F.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Carver, M.; Curry, D.; Das, S.; De Gruttola, M.; Di Giovanni, G. P.; Field, R. D.; Fisher, M.; Furic, I. K.; Hugon, J.; Konigsberg, J.; Korytov, A.; Kypreos, T.; Low, J. F.; Matchev, K.; Milenovic, P.; Mitselmakher, G.; Muniz, L.; Rinkevicius, A.; Shchutska, L.; Snowball, M.; Sperka, D.; Yelton, J.; Zakaria, M.; Hewamanage, S.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Adams, T.; Askew, A.; Bochenek, J.; Diamond, B.; Haas, J.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Prosper, H.; Veeraraghavan, V.; Weinberg, M.; Baarmand, M. M.; Hohlmann, M.; Kalakhety, H.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Bazterra, V. E.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Khalatyan, S.; Kurt, P.; Moon, D. H.; O'Brien, C.; Silkworth, C.; Turner, P.; Varelas, N.; Bilki, B.; Clarida, W.; Dilsiz, K.; Duru, F.; Haytmyradov, M.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Rahmat, R.; Sen, S.; Tan, P.; Tiras, E.; Wetzel, J.; Yi, K.; Barnett, B. A.; Blumenfeld, B.; Bolognesi, S.; Fehling, D.; Gritsan, A. V.; Maksimovic, P.; Martin, C.; Swartz, M.; Baringer, P.; Bean, A.; Benelli, G.; Bruner, C.; Kenny, R. P., III; Malek, M.; Murray, M.; Noonan, D.; Sanders, S.; Sekaric, J.; Stringer, R.; Wang, Q.; Wood, J. S.; Chakaberia, I.; Ivanov, A.; Khalil, S.; Makouski, M.; Maravin, Y.; Saini, L. K.; Shrestha, S.; Skhirtladze, N.; Svintradze, I.; Gronberg, J.; Lange, D.; Rebassoo, F.; Wright, D.; Baden, A.; Belloni, A.; Calvert, B.; Eno, S. C.; Gomez, J. A.; Hadley, N. J.; Kellogg, R. G.; Kolberg, T.; Lu, Y.; Marionneau, M.; Mignerey, A. C.; Pedro, K.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Apyan, A.; Barbieri, R.; Bauer, G.; Busza, W.; Cali, I. A.; Chan, M.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Gulhan, D.; Klute, M.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Ma, T.; Paus, C.; Ralph, D.; Roland, C.; Roland, G.; Stephans, G. S. F.; Stöckli, F.; Sumorok, K.; Velicanu, D.; Veverka, J.; Wyslouch, B.; Yang, M.; Zanetti, M.; Zhukova, V.; Dahmes, B.; Gude, A.; Kao, S. C.; Klapoetke, K.; Kubota, Y.; Mans, J.; Pastika, N.; Rusack, R.; Singovsky, A.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Bose, S.; Claes, D. R.; Dominguez, A.; Gonzalez Suarez, R.; Keller, J.; Knowlton, D.; Kravchenko, I.; Lazo-Flores, J.; Malik, S.; Meier, F.; Snow, G. R.; Zvada, M.; Dolen, J.; Godshalk, A.; Iashvili, I.; Kharchilava, A.; Kumar, A.; Rappoccio, S.; Alverson, G.; Barberis, E.; Baumgartel, D.; Chasco, M.; Haley, J.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Trocino, D.; Wang, R.-J.; Wood, D.; Zhang, J.; Hahn, K. A.; Kubik, A.; Mucia, N.; Odell, N.; Pollack, B.; Pozdnyakov, A.; Schmitt, M.; Stoynev, S.; Sung, K.; Velasco, M.; Won, S.; Brinkerhoff, A.; Chan, K. M.; Drozdetskiy, A.; Hildreth, M.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Luo, W.; Lynch, S.; Marinelli, N.; Pearson, T.; Planer, M.; Ruchti, R.; Valls, N.; Wayne, M.; Wolf, M.; Woodard, A.; Antonelli, L.; Brinson, J.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Hart, A.; Hill, C.; Hughes, R.; Kotov, K.; Ling, T. Y.; Puigh, D.; Rodenburg, M.; Smith, G.; Winer, B. L.; Wolfe, H.; Wulsin, H. W.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Hunt, A.; Koay, S. A.; Lujan, P.; Marlow, D.; Medvedeva, T.; Mooney, M.; Olsen, J.; Piroué, P.; Quan, X.; Saka, H.; Stickland, D.; Tully, C.; Werner, J. S.; Zuranski, A.; Brownson, E.; Mendez, H.; Ramirez Vargas, J. E.; Barnes, V. E.; Benedetti, D.; Bortoletto, D.; De Mattia, M.; Gutay, L.; Hu, Z.; Jha, M. K.; Jones, M.; Jung, K.; Kress, M.; Leonardo, N.; Lopes Pegna, D.; Maroussov, V.; Miller, D. H.; Neumeister, N.; Radburn-Smith, B. C.; Shi, X.; Shipsey, I.; Silvers, D.; Svyatkovskiy, A.; Wang, F.; Xie, W.; Xu, L.; Yoo, H. D.; Zablocki, J.; Zheng, Y.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Ecklund, K. M.; Geurts, F. J. M.; Li, W.; Michlin, B.; Padley, B. P.; Redjimi, R.; Roberts, J.; Zabel, J.; Betchart, B.; Bodek, A.; Covarelli, R.; de Barbaro, P.; Demina, R.; Eshaq, Y.; Ferbel, T.; Garcia-Bellido, A.; Goldenzweig, P.; Han, J.; Harel, A.; Khukhunaishvili, A.; Korjenevski, S.; Petrillo, G.; Vishnevskiy, D.; Ciesielski, R.; Demortier, L.; Goulianos, K.; Lungu, G.; Mesropian, C.; Arora, S.; Barker, A.; Chou, J. P.; Contreras-Campana, C.; Contreras-Campana, E.; Duggan, D.; Ferencek, D.; Gershtein, Y.; Gray, R.; Halkiadakis, E.; Hidas, D.; Kaplan, S.; Lath, A.; Panwalkar, S.; Park, M.; Patel, R.; Salur, S.; Schnetzer, S.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Rose, K.; Spanier, S.; York, A.; Bouhali, O.; Castaneda Hernandez, A.; Eusebi, R.; Flanagan, W.; Gilmore, J.; Kamon, T.; Khotilovich, V.; Krutelyov, V.; Montalvo, R.; Osipenkov, I.; Pakhotin, Y.; Perloff, A.; Roe, J.; Rose, A.; Safonov, A.; Suarez, I.; Tatarinov, A.; Akchurin, N.; Cowden, C.; Damgov, J.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Kovitanggoon, K.; Kunori, S.; Lee, S. W.; Libeiro, T.; Volobouev, I.; Appelt, E.; Delannoy, A. G.; Greene, S.; Gurrola, A.; Johns, W.; Maguire, C.; Mao, Y.; Melo, A.; Sharma, M.; Sheldon, P.; Snook, B.; Tuo, S.; Velkovska, J.; Arenton, M. W.; Boutle, S.; Cox, B.; Francis, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Lin, C.; Neu, C.; Wood, J.; Clarke, C.; Harr, R.; Karchin, P. E.; Kottachchi Kankanamge Don, C.; Lamichhane, P.; Sturdy, J.; Belknap, D. A.; Carlsmith, D.; Cepeda, M.; Dasu, S.; Dodd, L.; Duric, S.; Friis, E.; Hall-Wilton, R.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Lazaridis, C.; Levine, A.; Loveless, R.; Mohapatra, A.; Ojalvo, I.; Perry, T.; Pierro, G. A.; Polese, G.; Ross, I.; Sarangi, T.; Savin, A.; Smith, W. H.; Taylor, D.; Verwilligen, P.; Vuosalo, C.; Woods, N.
2015-06-01
A search is presented for quark contact interactions and extra spatial dimensions in proton-proton collisions at √{ s} = 8 TeV using dijet angular distributions. The search is based on a data set corresponding to an integrated luminosity of 19.7 fb-1 collected by the CMS detector at the CERN LHC. Dijet angular distributions are found to be in agreement with the perturbative QCD predictions that include electroweak corrections. Limits on the contact interaction scale from a variety of models at next-to-leading order in QCD corrections are obtained. A benchmark model in which only left-handed quarks participate is excluded up to a scale of 9.0 (11.7) TeV for destructive (constructive) interference at 95% confidence level. Lower limits between 5.9 and 8.4 TeV on the scale of virtual graviton exchange are extracted for the Arkani-Hamed-Dimopoulos-Dvali model of extra spatial dimensions.
Mrochen, Michael; Schelling, Urs; Wuellner, Christian; Donitzky, Christof
2009-02-01
To investigate the effect of temporal and spatial distributions of laser spots (scan sequences) on the corneal surface quality after ablation and the maximum ablation of a given refractive correction after photoablation with a high-repetition-rate scanning-spot laser. IROC AG, Zurich, Switzerland, and WaveLight AG, Erlangen, Germany. Bovine corneas and poly(methyl methacrylate) (PMMA) plates were photoablated using a 1050 Hz excimer laser prototype for corneal laser surgery. Four temporal and spatial spot distributions (scan sequences) with different temporal overlapping factors were created for 3 myopic, 3 hyperopic, and 3 phototherapeutic keratectomy ablation profiles. Surface quality and maximum ablation depth were measured using a surface profiling system. The surface quality factor increased (rough surfaces) as the amount of temporal overlapping in the scan sequence and the amount of correction increased. The rise in surface quality factor was less for bovine corneas than for PMMA. The scan sequence might cause systematic substructures at the surface of the ablated material depending on the overlapping factor. The maximum ablation varied within the scan sequence. The temporal and spatial distribution of the laser spots (scan sequence) during a corneal laser procedure affected the surface quality and maximum ablation depth of the ablation profile. Corneal laser surgery could theoretically benefit from smaller spot sizes and higher repetition rates. The temporal and spatial spot distributions are relevant to achieving these aims.
Removing the Impact of Correlated PSF Uncertainties in Weak Lensing
NASA Astrophysics Data System (ADS)
Lu, Tianhuan; Zhang, Jun; Dong, Fuyu; Li, Yingke; Liu, Dezi; Fu, Liping; Li, Guoliang; Fan, Zuhui
2018-05-01
Accurate reconstruction of the spatial distributions of the point-spread function (PSF) is crucial for high precision cosmic shear measurements. Nevertheless, current methods are not good at recovering the PSF fluctuations of high spatial frequencies. In general, the residual PSF fluctuations are spatially correlated, and therefore can significantly contaminate the correlation functions of the weak lensing signals. We propose a method to correct for this contamination statistically, without any assumptions on the PSF and galaxy morphologies or their spatial distribution. We demonstrate our idea with the data from the W2 field of CFHTLenS.
NASA Astrophysics Data System (ADS)
Hering, Julian; Waller, Erik H.; von Freymann, Georg
2017-02-01
Since a large number of optical systems and devices are based on differently shaped focal intensity distributions (point-spread-functions, PSF), the PSF's quality is crucial for the application's performance. E.g., optical tweezers, optical potentials for trapping of ultracold atoms as well as stimulated-emission-depletion (STED) based microscopy and lithography rely on precisely controlled intensity distributions. However, especially in high numerical aperture (NA) systems, such complex laser modes are easily distorted by aberrations leading to performance losses. Although different approaches addressing phase retrieval algorithms have been recently presented[1-3], fast and automated aberration compensation for a broad variety of complex shaped PSFs in high NA systems is still missing. Here, we report on a Gerchberg-Saxton[4] based algorithm (GSA) for automated aberration correction of arbitrary PSFs, especially for high NA systems. Deviations between the desired target intensity distribution and the three-dimensionally (3D) scanned experimental focal intensity distribution are used to calculate a correction phase pattern. The target phase distribution plus the correction pattern are displayed on a phase-only spatial-light-modulator (SLM). Focused by a high NA objective, experimental 3D scans of several intensity distributions allow for characterization of the algorithms performance: aberrations are reliably identified and compensated within less than 10 iterations. References 1. B. M. Hanser, M. G. L. Gustafsson, D. A. Agard, and J. W. Sedat, "Phase-retrieved pupil functions in wide-field fluorescence microscopy," J. of Microscopy 216(1), 32-48 (2004). 2. A. Jesacher, A. Schwaighofer, S. Frhapter, C. Maurer, S. Bernet, and M. Ritsch-Marte, "Wavefront correction of spatial light modulators using an optical vortex image," Opt. Express 15(9), 5801-5808 (2007). 3. A. Jesacher and M. J. Booth, "Parallel direct laser writing in three dimensions with spatially dependent aberration correction," Opt. Express 18(20), 21090-21099 (2010). 4. R. W. Gerchberg and W. O. Saxton, "A practical algorithm for the determination of the phase from image and diffraction plane pictures," Optik 35(2), 237-246 (1972).
Hayes, Mark A.; Ozenberger, Katharine; Cryan, Paul M.; Wunder, Michael B.
2015-01-01
Bat specimens held in natural history museum collections can provide insights into the distribution of species. However, there are several important sources of spatial error associated with natural history specimens that may influence the analysis and mapping of bat species distributions. We analyzed the importance of geographic referencing and error correction in species distribution modeling (SDM) using occurrence records of hoary bats (Lasiurus cinereus). This species is known to migrate long distances and is a species of increasing concern due to fatalities documented at wind energy facilities in North America. We used 3,215 museum occurrence records collected from 1950–2000 for hoary bats in North America. We compared SDM performance using five approaches: generalized linear models, multivariate adaptive regression splines, boosted regression trees, random forest, and maximum entropy models. We evaluated results using three SDM performance metrics (AUC, sensitivity, and specificity) and two data sets: one comprised of the original occurrence data, and a second data set consisting of these same records after the locations were adjusted to correct for identifiable spatial errors. The increase in precision improved the mean estimated spatial error associated with hoary bat records from 5.11 km to 1.58 km, and this reduction in error resulted in a slight increase in all three SDM performance metrics. These results provide insights into the importance of geographic referencing and the value of correcting spatial errors in modeling the distribution of a wide-ranging bat species. We conclude that the considerable time and effort invested in carefully increasing the precision of the occurrence locations in this data set was not worth the marginal gains in improved SDM performance, and it seems likely that gains would be similar for other bat species that range across large areas of the continent, migrate, and are habitat generalists.
Wiegand, Thorsten; Lehmann, Sebastian; Huth, Andreas; Fortin, Marie‐Josée
2016-01-01
Abstract Aim It has been recently suggested that different ‘unified theories of biodiversity and biogeography’ can be characterized by three common ‘minimal sufficient rules’: (1) species abundance distributions follow a hollow curve, (2) species show intraspecific aggregation, and (3) species are independently placed with respect to other species. Here, we translate these qualitative rules into a quantitative framework and assess if these minimal rules are indeed sufficient to predict multiple macroecological biodiversity patterns simultaneously. Location Tropical forest plots in Barro Colorado Island (BCI), Panama, and in Sinharaja, Sri Lanka. Methods We assess the predictive power of the three rules using dynamic and spatial simulation models in combination with census data from the two forest plots. We use two different versions of the model: (1) a neutral model and (2) an extended model that allowed for species differences in dispersal distances. In a first step we derive model parameterizations that correctly represent the three minimal rules (i.e. the model quantitatively matches the observed species abundance distribution and the distribution of intraspecific aggregation). In a second step we applied the parameterized models to predict four additional spatial biodiversity patterns. Results Species‐specific dispersal was needed to quantitatively fulfil the three minimal rules. The model with species‐specific dispersal correctly predicted the species–area relationship, but failed to predict the distance decay, the relationship between species abundances and aggregations, and the distribution of a spatial co‐occurrence index of all abundant species pairs. These results were consistent over the two forest plots. Main conclusions The three ‘minimal sufficient’ rules only provide an incomplete approximation of the stochastic spatial geometry of biodiversity in tropical forests. The assumption of independent interspecific placements is most likely violated in many forests due to shared or distinct habitat preferences. Furthermore, our results highlight missing knowledge about the relationship between species abundances and their aggregation. PMID:27667967
One-loop gravitational wave spectrum in de Sitter spacetime
NASA Astrophysics Data System (ADS)
Fröb, Markus B.; Roura, Albert; Verdaguer, Enric
2012-08-01
The two-point function for tensor metric perturbations around de Sitter spacetime including one-loop corrections from massless conformally coupled scalar fields is calculated exactly. We work in the Poincaré patch (with spatially flat sections) and employ dimensional regularization for the renormalization process. Unlike previous studies we obtain the result for arbitrary time separations rather than just equal times. Moreover, in contrast to existing results for tensor perturbations, ours is manifestly invariant with respect to the subgroup of de Sitter isometries corresponding to a simultaneous time translation and rescaling of the spatial coordinates. Having selected the right initial state for the interacting theory via an appropriate iepsilon prescription is crucial for that. Finally, we show that although the two-point function is a well-defined spacetime distribution, the equal-time limit of its spatial Fourier transform is divergent. Therefore, contrary to the well-defined distribution for arbitrary time separations, the power spectrum is strictly speaking ill-defined when loop corrections are included.
Reliability Correction for Functional Connectivity: Theory and Implementation
Mueller, Sophia; Wang, Danhong; Fox, Michael D.; Pan, Ruiqi; Lu, Jie; Li, Kuncheng; Sun, Wei; Buckner, Randy L.; Liu, Hesheng
2016-01-01
Network properties can be estimated using functional connectivity MRI (fcMRI). However, regional variation of the fMRI signal causes systematic biases in network estimates including correlation attenuation in regions of low measurement reliability. Here we computed the spatial distribution of fcMRI reliability using longitudinal fcMRI datasets and demonstrated how pre-estimated reliability maps can correct for correlation attenuation. As a test case of reliability-based attenuation correction we estimated properties of the default network, where reliability was significantly lower than average in the medial temporal lobe and higher in the posterior medial cortex, heterogeneity that impacts estimation of the network. Accounting for this bias using attenuation correction revealed that the medial temporal lobe’s contribution to the default network is typically underestimated. To render this approach useful to a greater number of datasets, we demonstrate that test-retest reliability maps derived from repeated runs within a single scanning session can be used as a surrogate for multi-session reliability mapping. Using data segments with different scan lengths between 1 and 30 min, we found that test-retest reliability of connectivity estimates increases with scan length while the spatial distribution of reliability is relatively stable even at short scan lengths. Finally, analyses of tertiary data revealed that reliability distribution is influenced by age, neuropsychiatric status and scanner type, suggesting that reliability correction may be especially important when studying between-group differences. Collectively, these results illustrate that reliability-based attenuation correction is an easily implemented strategy that mitigates certain features of fMRI signal nonuniformity. PMID:26493163
A Quantile Mapping Bias Correction Method Based on Hydroclimatic Classification of the Guiana Shield
Ringard, Justine; Seyler, Frederique; Linguet, Laurent
2017-01-01
Satellite precipitation products (SPPs) provide alternative precipitation data for regions with sparse rain gauge measurements. However, SPPs are subject to different types of error that need correction. Most SPP bias correction methods use the statistical properties of the rain gauge data to adjust the corresponding SPP data. The statistical adjustment does not make it possible to correct the pixels of SPP data for which there is no rain gauge data. The solution proposed in this article is to correct the daily SPP data for the Guiana Shield using a novel two set approach, without taking into account the daily gauge data of the pixel to be corrected, but the daily gauge data from surrounding pixels. In this case, a spatial analysis must be involved. The first step defines hydroclimatic areas using a spatial classification that considers precipitation data with the same temporal distributions. The second step uses the Quantile Mapping bias correction method to correct the daily SPP data contained within each hydroclimatic area. We validate the results by comparing the corrected SPP data and daily rain gauge measurements using relative RMSE and relative bias statistical errors. The results show that analysis scale variation reduces rBIAS and rRMSE significantly. The spatial classification avoids mixing rainfall data with different temporal characteristics in each hydroclimatic area, and the defined bias correction parameters are more realistic and appropriate. This study demonstrates that hydroclimatic classification is relevant for implementing bias correction methods at the local scale. PMID:28621723
Ringard, Justine; Seyler, Frederique; Linguet, Laurent
2017-06-16
Satellite precipitation products (SPPs) provide alternative precipitation data for regions with sparse rain gauge measurements. However, SPPs are subject to different types of error that need correction. Most SPP bias correction methods use the statistical properties of the rain gauge data to adjust the corresponding SPP data. The statistical adjustment does not make it possible to correct the pixels of SPP data for which there is no rain gauge data. The solution proposed in this article is to correct the daily SPP data for the Guiana Shield using a novel two set approach, without taking into account the daily gauge data of the pixel to be corrected, but the daily gauge data from surrounding pixels. In this case, a spatial analysis must be involved. The first step defines hydroclimatic areas using a spatial classification that considers precipitation data with the same temporal distributions. The second step uses the Quantile Mapping bias correction method to correct the daily SPP data contained within each hydroclimatic area. We validate the results by comparing the corrected SPP data and daily rain gauge measurements using relative RMSE and relative bias statistical errors. The results show that analysis scale variation reduces rBIAS and rRMSE significantly. The spatial classification avoids mixing rainfall data with different temporal characteristics in each hydroclimatic area, and the defined bias correction parameters are more realistic and appropriate. This study demonstrates that hydroclimatic classification is relevant for implementing bias correction methods at the local scale.
NASA Astrophysics Data System (ADS)
Tamura, K.; Jansen, R. A.; Eskridge, P. B.; Cohen, S. H.; Windhorst, R. A.
2010-06-01
We present the results of a study of the late-type spiral galaxy NGC 0959, before and after application of the pixel-based dust extinction correction described in Tamura et al. (Paper I). Galaxy Evolution Explorer far-UV, and near-UV, ground-based Vatican Advanced Technology Telescope, UBVR, and Spitzer/Infrared Array Camera 3.6, 4.5, 5.8, and 8.0 μm images are studied through pixel color-magnitude diagrams and pixel color-color diagrams (pCCDs). We define groups of pixels based on their distribution in a pCCD of (B - 3.6 μm) versus (FUV - U) colors after extinction correction. In the same pCCD, we trace their locations before the extinction correction was applied. This shows that selecting pixel groups is not meaningful when using colors uncorrected for dust. We also trace the distribution of the pixel groups on a pixel coordinate map of the galaxy. We find that the pixel-based (two-dimensional) extinction correction is crucial for revealing the spatial variations in the dominant stellar population, averaged over each resolution element. Different types and mixtures of stellar populations, and galaxy structures such as a previously unrecognized bar, become readily discernible in the extinction-corrected pCCD and as coherent spatial structures in the pixel coordinate map.
Detecting magnetic ordering with atomic size electron probes
Idrobo, Juan Carlos; Rusz, Ján; Spiegelberg, Jakob; ...
2016-05-27
While magnetism originates at the atomic scale, the existing spectroscopic techniques sensitive to magnetic signals only produce spectra with spatial resolution on a larger scale. However, recently, it has been theoretically argued that atomic size electron probes with customized phase distributions can detect magnetic circular dichroism. Here, we report a direct experimental real-space detection of magnetic circular dichroism in aberration-corrected scanning transmission electron microscopy (STEM). Using an atomic size-aberrated electron probe with a customized phase distribution, we reveal the checkerboard antiferromagnetic ordering of Mn moments in LaMnAsO by observing a dichroic signal in the Mn L-edge. The novel experimental setupmore » presented here, which can easily be implemented in aberration-corrected STEM, opens new paths for probing dichroic signals in materials with unprecedented spatial resolution.« less
NASA Astrophysics Data System (ADS)
Sorba, Robert; Sawicki, Marcin
2018-05-01
We perform spatially resolved, pixel-by-pixel Spectral Energy Distribution (SED) fitting on galaxies up to z ˜ 2.5 in the Hubble eXtreme Deep Field (XDF). Comparing stellar mass estimates from spatially resolved and spatially unresolved photometry we find that unresolved masses can be systematically underestimated by factors of up to 5. The ratio of the unresolved to resolved mass measurement depends on the galaxy's specific star formation rate (sSFR): at low sSFRs the bias is small, but above sSFR ˜ 10-9.5 yr-1 the discrepancy increases rapidly such that galaxies with sSFRs ˜ 10-8 yr-1 have unresolved mass estimates of only one-half to one-fifth of the resolved value. This result indicates that stellar masses estimated from spatially unresolved data sets need to be systematically corrected, in some cases by large amounts, and we provide an analytic prescription for applying this correction. We show that correcting stellar mass measurements for this bias changes the normalization and slope of the star-forming main sequence and reduces its intrinsic width; most dramatically, correcting for the mass bias increases the stellar mass density of the Universe at high redshift and can resolve the long-standing discrepancy between the directly measured cosmic SFR density at z ≳ 1 and that inferred from stellar mass densities (`the missing mass problem').
Atkinson, Samuel F; Sarkar, Sahotra; Aviña, Aldo; Schuermann, Jim A; Williamson, Phillip
2012-11-01
The spatial distribution of Dermacentor variabilis, the most commonly identified vector of the bacterium Rickettsia rickettsii which causes Rocky Mountain spotted fever (RMSF) in humans, and the spatial distribution of RMSF, have not been previously studied in the south central United States of America, particularly in Texas. From an epidemiological perspective, one would tend to hypothesise that there would be a high degree of spatial concordance between the habitat suitability for the tick and the incidence of the disease. Both maximum-entropy modelling of the tick's habitat suitability and spatially adaptive filters modelling of the human incidence of RMSF disease provide reliable portrayals of the spatial distributions of these phenomenons. Even though rates of human cases of RMSF in Texas and rates of Dermacentor ticks infected with Rickettsia bacteria are both relatively low in Texas, the best data currently available allows a preliminary indication that the assumption of high levels of spatial concordance would not be correct in Texas (Kappa coefficient of agreement = 0.17). It will take substantially more data to provide conclusive findings, and to understand the results reported here, but this study provides an approach to begin understanding the discrepancy.
Development of an algorithm for corneal reshaping with a scanning laser beam
NASA Astrophysics Data System (ADS)
Shen, Jin-Hui; Söderberg, Per; Matsui, Takaaki; Manns, Fabrice; Parel, Jean-Marie
1995-07-01
The corneal-ablation rate, the beam-intensity distribution, and the initial and the desired corneal topographies are used to calculate a spatial distribution map of laser pulses. The optimal values of the parameters are determined with a computer model, for a system that produces 213-nm radiation with a Gaussian beam-intensity distribution and a peak radiant exposure of 400 mJ/cm2. The model shows that with a beam diameter of 0.5 mm, an overlap of 80%, and a 5-mm treatment zone, the roughness is less than 6% of the central ablation depth, the refractive error after correction is less than 0.1 D for corrections of myopia of 1, 3, and 6 D and less than 0.4 D for a correction of myopia of 10 D, and the number of pulses per diopter of
NASA Astrophysics Data System (ADS)
Tanabe, Ayano; Hibi, Terumasa; Ipponjima, Sari; Matsumoto, Kenji; Yokoyama, Masafumi; Kurihara, Makoto; Hashimoto, Nobuyuki; Nemoto, Tomomi
2016-12-01
All aberrations produced inside a biospecimen can degrade the quality of a three-dimensional image in two-photon excitation laser scanning microscopy. Previously, we developed a transmissive liquid-crystal device to correct spherical aberrations that improved the image quality of a fixed-mouse-brain slice treated with an optical clearing reagent. In this study, we developed a transmissive device that corrects primary coma aberration and astigmatism. The motivation for this study is that asymmetric aberration can be induced by the shape of a biospecimen and/or by a complicated refractive-index distribution in a sample; this can considerably degrade optical performance even near the sample surface. The device's performance was evaluated by observing fluorescence beads. The device was inserted between the objective lens and microscope revolver and succeeded in improving the spatial resolution and fluorescence signal of a bead image that was originally degraded by asymmetric aberration. Finally, we implemented the device for observing a fixed whole mouse brain with a sloping surface shape and complicated internal refractive-index distribution. The correction with the device improved the spatial resolution and increased the fluorescence signal by ˜2.4×. The device can provide a simple approach to acquiring higher-quality images of biospecimens.
Diversity and distribution of parasitic angiosperms in China.
Zhang, Guangfu; Li, Qian; Sun, Shucun
2018-05-01
Parasitic plants are an important component of vegetation worldwide, but their diversity and distribution in China have not been systematically reported. This study aimed to (1) explore floral characteristics of China's parasitic plants, (2) map spatial distribution of diversity of these species, and (3) explore factors influencing the distribution pattern. We compiled a nationwide species list of parasitic plants in China, and for each species, we recorded its phylogeny, endemism, and life form (e.g., herb vs. shrub; hemiparasite vs. holoparasite). Species richness and area-corrected species richness were calculated for 28 provinces, covering 98.89% of China's terrestrial area. Regression analyses were performed to determine relationships between provincial area-corrected species richness of parasitic plants and provincial total species richness (including nonparasitic plants) and physical settings (altitude, midlongitude, and midlatitude). A total of 678 species of parasitic angiosperms are recorded in China, 63.13% of which are endemic. Of the total, 59.73% (405 species) are perennials, followed by shrubs/subshrubs (14.75%) and vines (1.47%). About 76.11% (516 species) are of root hemiparasites, higher than that of stem parasites (100, 14.75%), root holoparasites (9.00%), and endophytic parasites (0.15%). A significant positive relationship is found between the area-corrected species richness and the total species richness, which has been previously demonstrated to increase with decreasing longitude and latitude. Moreover, more parasitic species are found in the southwest high-altitude areas than low areas. Consistently, the area-corrected species richness increases with increasing altitude, decreasing latitude, and decreasing longitude, as indicated by regression analyses. China is rich in parasitic flora with a high proportion of endemic species. Perennials and root hemiparasites are the dominant types. The spatial distribution of parasitic plants is largely heterogeneous, with more species living in southwest China, similar to the distribution pattern of Chinese angiosperms. The positive relationship between parasitic and nonparasitic plant species richness should be addressed in the future.
NASA Astrophysics Data System (ADS)
Mamalakis, Antonios; Langousis, Andreas; Deidda, Roberto; Marrocu, Marino
2017-03-01
Distribution mapping has been identified as the most efficient approach to bias-correct climate model rainfall, while reproducing its statistics at spatial and temporal resolutions suitable to run hydrologic models. Yet its implementation based on empirical distributions derived from control samples (referred to as nonparametric distribution mapping) makes the method's performance sensitive to sample length variations, the presence of outliers, the spatial resolution of climate model results, and may lead to biases, especially in extreme rainfall estimation. To address these shortcomings, we propose a methodology for simultaneous bias correction and high-resolution downscaling of climate model rainfall products that uses: (a) a two-component theoretical distribution model (i.e., a generalized Pareto (GP) model for rainfall intensities above a specified threshold u*, and an exponential model for lower rainrates), and (b) proper interpolation of the corresponding distribution parameters on a user-defined high-resolution grid, using kriging for uncertain data. We assess the performance of the suggested parametric approach relative to the nonparametric one, using daily raingauge measurements from a dense network in the island of Sardinia (Italy), and rainfall data from four GCM/RCM model chains of the ENSEMBLES project. The obtained results shed light on the competitive advantages of the parametric approach, which is proved more accurate and considerably less sensitive to the characteristics of the calibration period, independent of the GCM/RCM combination used. This is especially the case for extreme rainfall estimation, where the GP assumption allows for more accurate and robust estimates, also beyond the range of the available data.
Evaluation of Statistical Downscaling Skill at Reproducing Extreme Events
NASA Astrophysics Data System (ADS)
McGinnis, S. A.; Tye, M. R.; Nychka, D. W.; Mearns, L. O.
2015-12-01
Climate model outputs usually have much coarser spatial resolution than is needed by impacts models. Although higher resolution can be achieved using regional climate models for dynamical downscaling, further downscaling is often required. The final resolution gap is often closed with a combination of spatial interpolation and bias correction, which constitutes a form of statistical downscaling. We use this technique to downscale regional climate model data and evaluate its skill in reproducing extreme events. We downscale output from the North American Regional Climate Change Assessment Program (NARCCAP) dataset from its native 50-km spatial resolution to the 4-km resolution of University of Idaho's METDATA gridded surface meterological dataset, which derives from the PRISM and NLDAS-2 observational datasets. We operate on the major variables used in impacts analysis at a daily timescale: daily minimum and maximum temperature, precipitation, humidity, pressure, solar radiation, and winds. To interpolate the data, we use the patch recovery method from the Earth System Modeling Framework (ESMF) regridding package. We then bias correct the data using Kernel Density Distribution Mapping (KDDM), which has been shown to exhibit superior overall performance across multiple metrics. Finally, we evaluate the skill of this technique in reproducing extreme events by comparing raw and downscaled output with meterological station data in different bioclimatic regions according to the the skill scores defined by Perkins et al in 2013 for evaluation of AR4 climate models. We also investigate techniques for improving bias correction of values in the tails of the distributions. These techniques include binned kernel density estimation, logspline kernel density estimation, and transfer functions constructed by fitting the tails with a generalized pareto distribution.
Analyses and assessments of span wise gust gradient data from NASA B-57B aircraft
NASA Technical Reports Server (NTRS)
Frost, Walter; Chang, Ho-Pen; Ringnes, Erik A.
1987-01-01
Analysis of turbulence measured across the airfoil of a Cambera B-57 aircraft is reported. The aircraft is instrumented with probes for measuring wind at both wing tips and at the nose. Statistical properties of the turbulence are reported. These consist of the standard deviations of turbulence measured by each individual probe, standard deviations and probability distribution of differences in turbulence measured between probes and auto- and two-point spatial correlations and spectra. Procedures associated with calculations of two-point spatial correlations and spectra utilizing data were addressed. Methods and correction procedures for assuring the accuracy of aircraft measured winds are also described. Results are found, in general, to agree with correlations existing in the literature. The velocity spatial differences fit a Gaussian/Bessel type probability distribution. The turbulence agrees with the von Karman turbulence correlation and with two-point spatial correlations developed from the von Karman correlation.
NASA Technical Reports Server (NTRS)
Burr, Devon M.; Bruno, Barbara C.; Lanagan, Peter D.; Glaze, Lori; Jaeger, Windy L.; Soare, Richard J.; Tseung, Jean-Michel Wan Bun; Skinner, James A. Jr.; Baloga, Stephen M.
2008-01-01
Fields of mesoscale raised rim depressions (MRRDs) of various origins are found on Earth and Mars. Examples include rootless cones, mud volcanoes, collapsed pingos, rimmed kettle holes, and basaltic ring structures. Correct identification of MRRDs on Mars is valuable because different MRRD types have different geologic and/or climatic implications and are often associated with volcanism and/or water, which may provide locales for biotic or prebiotic activity. In order to facilitate correct identification of fields of MRRDs on Mars and their implications, this work provides a review of common terrestrial MRRD types that occur in fields. In this review, MRRDs by formation mechanism, including hydrovolcanic (phreatomagmatic cones, basaltic ring structures), sedimentological (mud volcanoes), and ice-related (pingos, volatile ice-block forms) mechanisms. For each broad mechanism, we present a comparative synopsis of (i) morphology and observations, (ii) physical formation processes, and (iii) published hypothesized locations on Mars. Because the morphology for MRRDs may be ambiguous, an additional tool is provided for distinguishing fields of MRRDs by origin on Mars, namely, spatial distribution analyses for MRRDs within fields on Earth. We find that MRRDs have both distinguishing and similar characteristics, and observation that applies both to their mesoscale morphology and to their spatial distribution statistics. Thus, this review provides tools for distinguishing between various MRRDs, while highlighting the utility of the multiple working hypotheses approach.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Garcia-Lechuga, M.; Laser Processing Group, Instituto de Óptica “Daza de Valdés,” CSIC, 28006-Madrid; Fuentes, L. M.
2014-10-07
We report a detailed characterization of the spatial resolution provided by two-photon absorption spectroscopy suited for plasma diagnosis via the 1S-2S transition of atomic hydrogen for optogalvanic detection and laser induced fluorescence (LIF). A precise knowledge of the spatial resolution is crucial for a correct interpretation of measurements, if the plasma parameters to be analysed undergo strong spatial variations. The present study is based on a novel approach which provides a reliable and realistic determination of the spatial resolution. Measured irradiance distribution of laser beam waists in the overlap volume, provided by a high resolution UV camera, are employed tomore » resolve coupled rate equations accounting for two-photon excitation, fluorescence decay and ionization. The resulting three-dimensional yield distributions reveal in detail the spatial resolution for optogalvanic and LIF detection and related saturation due to depletion. Two-photon absorption profiles broader than the Fourier transform-limited laser bandwidth are also incorporated in the calculations. The approach allows an accurate analysis of the spatial resolution present in recent and future measurements.« less
Multichannel blind deconvolution of spatially misaligned images.
Sroubek, Filip; Flusser, Jan
2005-07-01
Existing multichannel blind restoration techniques assume perfect spatial alignment of channels, correct estimation of blur size, and are prone to noise. We developed an alternating minimization scheme based on a maximum a posteriori estimation with a priori distribution of blurs derived from the multichannel framework and a priori distribution of original images defined by the variational integral. This stochastic approach enables us to recover the blurs and the original image from channels severely corrupted by noise. We observe that the exact knowledge of the blur size is not necessary, and we prove that translation misregistration up to a certain extent can be automatically removed in the restoration process.
Evaluation of a spatially-distributed Thornthwaite water-balance model
DOE Office of Scientific and Technical Information (OSTI.GOV)
Lough, J.A.
1993-03-01
A small watershed of low relief in coastal New Hampshire was divided into hydrologic sub-areas in a geographic information system on the basis of soils, sub-basins and remotely-sensed landcover. Three variables were spatially modeled for input to 49 individual water-balances: available water content of the root zone, water input and potential evapotranspiration (PET). The individual balances were weight-summed to generate the aggregate watershed-balance, which saw 9% (48--50 mm) less annual actual-evapotranspiration (AET) compared to a lumped approach. Analysis of streamflow coefficients suggests that the spatially-distributed approach is more representative of the basin dynamics. Variation of PET by landcover accounted formore » the majority of the 9% AET reduction. Variation of soils played a near-negligible role. As a consequence of the above points, estimates of landcover proportions and annual PET by landcover are sufficient to correct a lumped water-balance in the Northeast. If remote sensing is used to estimate the landcover area, a sensor with a high spatial resolution is required. Finally, while the lower Thornthwaite model has conceptual limitations for distributed application, the upper Thornthwaite model is highly adaptable to distributed problems and may prove useful in many earth-system models.« less
TMPA Products 3B42RT & 3B42V6: Evaluation and Application in Qinghai-Tibet Plateau
NASA Astrophysics Data System (ADS)
Hao, Z.; Sun, L.; Wang, J.
2012-04-01
Hydrological researchers in Qinghai-Tibet Plateau tend to be haunted by deficiency of station gauged precipitation data for the sparse and uneven distribution of local meteorological stations. Fortunately, alternative data can be obtained from TRMM (Tropic Rainfall Measurement Mission) satellite. Preliminary evaluation and necessary correction of TRMM satellite rainfall products is required for the sake of reliability and suitability considering that TRMM precipitation is unconventional and natural condition in Qinghai-Tibet Plateau is unusually complicated. 3B42RT and 3B42V6 products from TRMM Multisatellite Precipitation Analysis(TMPA) are evaluated in northeast Qinghai-Tibet Plateau with 50 stations quality-controlled gauged daily precipitation as the benchmark precipitation set. It is found that the RT data overestimates the actual precipitation greatly while V6 only overestimates it slightly. RT data shows different seasonal and inter-annual accuracies. Summer and autumn see better accuracies than winter and spring and wet years see higher accuracies than dry years. Latitude is believed to be an important factor that influences the accuracy of satellite precipitation. Both RT and V6 can reflect the general pattern of the spatial distribution of precipitation even though RT overestimates the quantity greatly. A new parameter, accumulated precipitation weight point (APWP), was introduced to describe the temporal-spatial pattern evolution of precipitation. The APWP of both RT and V6 were moving from south to north in the past decade, but they are all in the west of station gauged precipitation APWP(s).V6 APWP track fit gauged precipitation perfectly while RT APWP track has over-exaggerated legs, indicating that spatial distribution of RT precipitation experienced unreasonable sharp changes. A practical and operational procedure to correct satellite precipitation data is developed. For RT, there are two steps. Step 1, the downscaling, original daily precipitation was multiplied by a ratio of its monthly satellite/station precipitation gauged precipitation. Step2, objective analysis, Barnes/Cressman successive correction as well as Optimal Interpolation was applied to refine the processed daily results. Step 1 is unnecessary for V6 correction. The accuracy of RT can be improved significantly and the spatial details of satellite precipitation can be obtained as much as possible while quite little improvement showed in V6 correction. Besides, the iteration of successive correction should not be more than twice and the ideal influence radius for Optimal Interpolation is R=5. The original/corrected RT and V6 data sets were used as precipitation inputs to drive a newly developed hydrological model DHM-SP in the headwater region of the Yellow river so as to assess their applicability in simulating the daily runoff. V6 simulation result is qualified even though it is uncorrected. The bias in RT is too much to make use of RT as model input directly while quite satisfied results can be derived from corrected RT input. The simulation results of corrected RT are even better than that of station gauged and V6.
NASA Astrophysics Data System (ADS)
Collados-Lara, Antonio-Juan; Pulido-Velazquez, David; Pardo-Iguzquiza, Eulogio
2017-04-01
Assessing impacts of potential future climate change scenarios in precipitation and temperature is essential to design adaptive strategies in water resources systems. The objective of this work is to analyze the possibilities of different statistical downscaling methods to generate future potential scenarios in an Alpine Catchment from historical data and the available climate models simulations performed in the frame of the CORDEX EU project. The initial information employed to define these downscaling approaches are the historical climatic data (taken from the Spain02 project for the period 1971-2000 with a spatial resolution of 12.5 Km) and the future series provided by climatic models in the horizon period 2071-2100 . We have used information coming from nine climate model simulations (obtained from five different Regional climate models (RCM) nested to four different Global Climate Models (GCM)) from the European CORDEX project. In our application we have focused on the Representative Concentration Pathways (RCP) 8.5 emissions scenario, which is the most unfavorable scenario considered in the fifth Assessment Report (AR5) by the Intergovernmental Panel on Climate Change (IPCC). For each RCM we have generated future climate series for the period 2071-2100 by applying two different approaches, bias correction and delta change, and five different transformation techniques (first moment correction, first and second moment correction, regression functions, quantile mapping using distribution derived transformation and quantile mapping using empirical quantiles) for both of them. Ensembles of the obtained series were proposed to obtain more representative potential future climate scenarios to be employed to study potential impacts. In this work we propose a non-equifeaseble combination of the future series giving more weight to those coming from models (delta change approaches) or combination of models and techniques that provides better approximation to the basic and drought statistic of the historical data. A multi-objective analysis using basic statistics (mean, standard deviation and asymmetry coefficient) and droughts statistics (duration, magnitude and intensity) has been performed to identify which models are better in terms of goodness of fit to reproduce the historical series. The drought statistics have been obtained from the Standard Precipitation index (SPI) series using the Theory of Runs. This analysis allows discriminate the best RCM and the best combination of model and correction technique in the bias-correction method. We have also analyzed the possibilities of using different Stochastic Weather Generators to approximate the basic and droughts statistics of the historical series. These analyses have been performed in our case study in a lumped and in a distributed way in order to assess its sensibility to the spatial scale. The statistic of the future temperature series obtained with different ensemble options are quite homogeneous, but the precipitation shows a higher sensibility to the adopted method and spatial scale. The global increment in the mean temperature values are 31.79 %, 31.79 %, 31.03 % and 31.74 % for the distributed bias-correction, distributed delta-change, lumped bias-correction and lumped delta-change ensembles respectively and in the precipitation they are -25.48 %, -28.49 %, -26.42 % and -27.35% respectively. Acknowledgments: This research work has been partially supported by the GESINHIMPADAPT project (CGL2013-48424-C2-2-R) with Spanish MINECO funds. We would also like to thank Spain02 and CORDEX projects for the data provided for this study and the R package qmap.
Bias-correction and Spatial Disaggregation for Climate Change Impact Assessments at a basin scale
NASA Astrophysics Data System (ADS)
Nyunt, Cho; Koike, Toshio; Yamamoto, Akio; Nemoto, Toshihoro; Kitsuregawa, Masaru
2013-04-01
Basin-scale climate change impact studies mainly rely on general circulation models (GCMs) comprising the related emission scenarios. Realistic and reliable data from GCM is crucial for national scale or basin scale impact and vulnerability assessments to build safety society under climate change. However, GCM fail to simulate regional climate features due to the imprecise parameterization schemes in atmospheric physics and coarse resolution scale. This study describes how to exclude some unsatisfactory GCMs with respect to focused basin, how to minimize the biases of GCM precipitation through statistical bias correction and how to cover spatial disaggregation scheme, a kind of downscaling, within in a basin. GCMs rejection is based on the regional climate features of seasonal evolution as a bench mark and mainly depends on spatial correlation and root mean square error of precipitation and atmospheric variables over the target region. Global Precipitation Climatology Project (GPCP) and Japanese 25-uear Reanalysis Project (JRA-25) are specified as references in figuring spatial pattern and error of GCM. Statistical bias-correction scheme comprises improvements of three main flaws of GCM precipitation such as low intensity drizzled rain days with no dry day, underestimation of heavy rainfall and inter-annual variability of local climate. Biases of heavy rainfall are conducted by generalized Pareto distribution (GPD) fitting over a peak over threshold series. Frequency of rain day error is fixed by rank order statistics and seasonal variation problem is solved by using a gamma distribution fitting in each month against insi-tu stations vs. corresponding GCM grids. By implementing the proposed bias-correction technique to all insi-tu stations and their respective GCM grid, an easy and effective downscaling process for impact studies at the basin scale is accomplished. The proposed method have been examined its applicability to some of the basins in various climate regions all over the world. The biases are controlled very well by using this scheme in all applied basins. After that, bias-corrected and downscaled GCM precipitation are ready to use for simulating the Water and Energy Budget based Distributed Hydrological Model (WEB-DHM) to analyse the stream flow change or water availability of a target basin under the climate change in near future. Furthermore, it can be investigated any inter-disciplinary studies such as drought, flood, food, health and so on.In summary, an effective and comprehensive statistical bias-correction method was established to fulfil the generative applicability of GCM scale to basin scale without difficulty. This gap filling also promotes the sound decision of river management in the basin with more reliable information to build the resilience society.
NASA Astrophysics Data System (ADS)
Tian, Qingjiu; Chen, Jing M.; Zheng, Guang; Xia, Xueqi; Chen, Junying
2006-09-01
Forest ecosystem is an important component of terrestrial ecosystem and plays an important role in global changes. Aboveground biomass (AGB) of forest ecosystem is an important factor in global carbon cycle studies. The purpose of this study was to retrieve the yearly Net Primary Productivity (NPP) of forest from the 8-days-interval MODIS-LAI images of a year and produce a yearly NPP distribution map. The LAI, DBH (diameter at breast height), tree height, and tree age field were measured in different 80 plots for Chinese fir, Masson pine, bamboo, broadleaf, mix forest in Liping County. Based on the DEM image and Landsat TM images acquired on May 14th, 2000, the geometric correction and terrain correction were taken. In addition, the "6S"model was used to gain the surface reflectance image. Then the correlation between Leaf Area Index (LAI) and Reduced Simple Ratio (RSR) was built. Combined with the Landcover map, forest stand map, the LAI, aboveground biomass, tree age map were produced respectively. After that, the 8-days- interval LAI images of a year, meteorology data, soil data, forest stand image and Landcover image were inputted into the BEPS model to get the NPP spatial distribution. At last, the yearly NPP spatial distribution map with 30m spatial resolution was produced. The values in those forest ecological parameters distribution maps were quite consistent with those of field measurements. So it's possible, feasible and time-saving to estimate forest ecological parameters at a large scale by using remote sensing.
NASA Astrophysics Data System (ADS)
Touhidul Mustafa, Syed Md.; Nossent, Jiri; Ghysels, Gert; Huysmans, Marijke
2017-04-01
Transient numerical groundwater flow models have been used to understand and forecast groundwater flow systems under anthropogenic and climatic effects, but the reliability of the predictions is strongly influenced by different sources of uncertainty. Hence, researchers in hydrological sciences are developing and applying methods for uncertainty quantification. Nevertheless, spatially distributed flow models pose significant challenges for parameter and spatially distributed input estimation and uncertainty quantification. In this study, we present a general and flexible approach for input and parameter estimation and uncertainty analysis of groundwater models. The proposed approach combines a fully distributed groundwater flow model (MODFLOW) with the DiffeRential Evolution Adaptive Metropolis (DREAM) algorithm. To avoid over-parameterization, the uncertainty of the spatially distributed model input has been represented by multipliers. The posterior distributions of these multipliers and the regular model parameters were estimated using DREAM. The proposed methodology has been applied in an overexploited aquifer in Bangladesh where groundwater pumping and recharge data are highly uncertain. The results confirm that input uncertainty does have a considerable effect on the model predictions and parameter distributions. Additionally, our approach also provides a new way to optimize the spatially distributed recharge and pumping data along with the parameter values under uncertain input conditions. It can be concluded from our approach that considering model input uncertainty along with parameter uncertainty is important for obtaining realistic model predictions and a correct estimation of the uncertainty bounds.
Barbee, David L; Flynn, Ryan T; Holden, James E; Nickles, Robert J; Jeraj, Robert
2010-01-01
Tumor heterogeneities observed in positron emission tomography (PET) imaging are frequently compromised of partial volume effects which may affect treatment prognosis, assessment, or future implementations such as biologically optimized treatment planning (dose painting). This paper presents a method for partial volume correction of PET-imaged heterogeneous tumors. A point source was scanned on a GE Discover LS at positions of increasing radii from the scanner’s center to obtain the spatially varying point spread function (PSF). PSF images were fit in three dimensions to Gaussian distributions using least squares optimization. Continuous expressions were devised for each Gaussian width as a function of radial distance, allowing for generation of the system PSF at any position in space. A spatially varying partial volume correction (SV-PVC) technique was developed using expectation maximization (EM) and a stopping criterion based on the method’s correction matrix generated for each iteration. The SV-PVC was validated using a standard tumor phantom and a tumor heterogeneity phantom, and was applied to a heterogeneous patient tumor. SV-PVC results were compared to results obtained from spatially invariant partial volume correction (SINV-PVC), which used directionally uniform three dimensional kernels. SV-PVC of the standard tumor phantom increased the maximum observed sphere activity by 55 and 40% for 10 and 13 mm diameter spheres, respectively. Tumor heterogeneity phantom results demonstrated that as net changes in the EM correction matrix decreased below 35%, further iterations improved overall quantitative accuracy by less than 1%. SV-PVC of clinically observed tumors frequently exhibited changes of ±30% in regions of heterogeneity. The SV-PVC method implemented spatially varying kernel widths and automatically determined the number of iterations for optimal restoration, parameters which are arbitrarily chosen in SINV-PVC. Comparing SV-PVC to SINV-PVC demonstrated that similar results could be reached using both methods, but large differences result for the arbitrary selection of SINV-PVC parameters. The presented SV-PVC method was performed without user intervention, requiring only a tumor mask as input. Research involving PET-imaged tumor heterogeneity should include correcting for partial volume effects to improve the quantitative accuracy of results. PMID:20009194
NASA Astrophysics Data System (ADS)
Sacha, Jan; Snehota, Michal; Jelinkova, Vladimira
2016-04-01
Information on spatial and temporal water and air distribution in a soil sample during hydrological processes is important for evaluating current and developing new water transport models. Modern imaging techniques such as neutron imaging (NI) allow relatively short acquisition times and high resolution of images. At the same time, the appropriate data processing has to be applied to obtain results free of bias and artifacts. In this study a ponded infiltration experiments were conducted on two soil samples packed into the quartz glass columns of inner diameter of 29 and 34 mm, respectively. First sample was prepared by packing of fine and coarse fractions of sand and the second sample was packed using coarse sand and disks of fine porous ceramic. Ponded infiltration experiments conducted on both samples were monitored by neutron radiography to produce two dimensional (2D) projection images during the transient phase of infiltration. During the steady state flow stage of experiments neutron tomography was utilized to obtain three-dimensional (3D) information on gradual water redistribution. The acquired radiographic images were normalized for background noise and spatial inhomogeneity of the detector, fluctuations of the neutron flux in time and for spatial inhomogeneity of the neutron beam. The radiograms of dry sample were subtracted from all subsequent radiograms to determine water thickness in the 2D projection images. All projections were corrected for beam hardening and neutron scattering by empirical method of Kang et al. (2013). Parameters of the correction method uses were identified by two different approaches. The first approach was based on fitting the NI derived water thickness representing the water filled region in the layer of water above the sample surface to actual water thickness. In the second approach the NI derived volume of water in the entire sample in given time was fitted to corresponding gravimetrically determined amount of water in the sample. Tomography images were reconstructed from the both corrected and uncorrected water thickness maps to obtain the 3D spatial distribution of water content within the sample. Without the correction the beam hardening and scattering effects overestimated the water content values close to the sample perimeter and underestimated the values close to the center of the sample, however the total water content of whole sample was the same in both cases.
Linard, Catherine; Lamarque, Pénélope; Heyman, Paul; Ducoffre, Geneviève; Luyasu, Victor; Tersago, Katrien; Vanwambeke, Sophie O; Lambin, Eric F
2007-05-02
Vector-borne and zoonotic diseases generally display clear spatial patterns due to different space-dependent factors. Land cover and land use influence disease transmission by controlling both the spatial distribution of vectors or hosts, and the probability of contact with susceptible human populations. The objective of this study was to combine environmental and socio-economic factors to explain the spatial distribution of two emerging human diseases in Belgium, Puumala virus (PUUV) and Lyme borreliosis. Municipalities were taken as units of analysis. Negative binomial regressions including a correction for spatial endogeneity show that the spatial distribution of PUUV and Lyme borreliosis infections are associated with a combination of factors linked to the vector and host populations, to human behaviours, and to landscape attributes. Both diseases are associated with the presence of forests, which are the preferred habitat for vector or host populations. The PUUV infection risk is higher in remote forest areas, where the level of urbanisation is low, and among low-income populations. The Lyme borreliosis transmission risk is higher in mixed landscapes with forests and spatially dispersed houses, mostly in wealthy peri-urban areas. The spatial dependence resulting from a combination of endogenous and exogenous processes could be accounted for in the model on PUUV but not for Lyme borreliosis. A large part of the spatial variation in disease risk can be explained by environmental and socio-economic factors. The two diseases not only are most prevalent in different regions but also affect different groups of people. Combining these two criteria may increase the efficiency of information campaigns through appropriate targeting.
Predicting the distribution of bed material accumulation using river network sediment budgets
NASA Astrophysics Data System (ADS)
Wilkinson, Scott N.; Prosser, Ian P.; Hughes, Andrew O.
2006-10-01
Assessing the spatial distribution of bed material accumulation in river networks is important for determining the impacts of erosion on downstream channel form and habitat and for planning erosion and sediment management. A model that constructs spatially distributed budgets of bed material sediment is developed to predict the locations of accumulation following land use change. For each link in the river network, GIS algorithms are used to predict bed material supply from gullies, river banks, and upstream tributaries and to compare total supply with transport capacity. The model is tested in the 29,000 km2 Murrumbidgee River catchment in southeast Australia. It correctly predicts the presence or absence of accumulation in 71% of river links, which is significantly better performance than previous models, which do not account for spatial variability in sediment supply and transport capacity. Representing transient sediment storage is important for predicting smaller accumulations. Bed material accumulation is predicted in 25% of the river network, indicating its importance as an environmental problem in Australia.
Local multiplicity adjustment for the spatial scan statistic using the Gumbel distribution.
Gangnon, Ronald E
2012-03-01
The spatial scan statistic is an important and widely used tool for cluster detection. It is based on the simultaneous evaluation of the statistical significance of the maximum likelihood ratio test statistic over a large collection of potential clusters. In most cluster detection problems, there is variation in the extent of local multiplicity across the study region. For example, using a fixed maximum geographic radius for clusters, urban areas typically have many overlapping potential clusters, whereas rural areas have relatively few. The spatial scan statistic does not account for local multiplicity variation. We describe a previously proposed local multiplicity adjustment based on a nested Bonferroni correction and propose a novel adjustment based on a Gumbel distribution approximation to the distribution of a local scan statistic. We compare the performance of all three statistics in terms of power and a novel unbiased cluster detection criterion. These methods are then applied to the well-known New York leukemia dataset and a Wisconsin breast cancer incidence dataset. © 2011, The International Biometric Society.
Local multiplicity adjustment for the spatial scan statistic using the Gumbel distribution
Gangnon, Ronald E.
2011-01-01
Summary The spatial scan statistic is an important and widely used tool for cluster detection. It is based on the simultaneous evaluation of the statistical significance of the maximum likelihood ratio test statistic over a large collection of potential clusters. In most cluster detection problems, there is variation in the extent of local multiplicity across the study region. For example, using a fixed maximum geographic radius for clusters, urban areas typically have many overlapping potential clusters, while rural areas have relatively few. The spatial scan statistic does not account for local multiplicity variation. We describe a previously proposed local multiplicity adjustment based on a nested Bonferroni correction and propose a novel adjustment based on a Gumbel distribution approximation to the distribution of a local scan statistic. We compare the performance of all three statistics in terms of power and a novel unbiased cluster detection criterion. These methods are then applied to the well-known New York leukemia dataset and a Wisconsin breast cancer incidence dataset. PMID:21762118
NASA Astrophysics Data System (ADS)
Delhaye, Robert; Rath, Volker; Jones, Alan G.; Muller, Mark R.; Reay, Derek
2017-05-01
Galvanic distortions of magnetotelluric (MT) data, such as the static-shift effect, are a known problem that can lead to incorrect estimation of resistivities and erroneous modelling of geometries with resulting misinterpretation of subsurface electrical resistivity structure. A wide variety of approaches have been proposed to account for these galvanic distortions, some depending on the target area, with varying degrees of success. The natural laboratory for our study is a hydraulically permeable volume of conductive sediment at depth, the internal resistivity structure of which can be used to estimate reservoir viability for geothermal purposes; however, static-shift correction is required in order to ensure robust and precise modelling accuracy.We present here a possible method to employ frequency-domain electromagnetic data in order to correct static-shift effects, illustrated by a case study from Northern Ireland. In our survey area, airborne frequency domain electromagnetic (FDEM) data are regionally available with high spatial density. The spatial distributions of the derived static-shift corrections are analysed and applied to the uncorrected MT data prior to inversion. Two comparative inversion models are derived, one with and one without static-shift corrections, with instructive results. As expected from the one-dimensional analogy of static-shift correction, at shallow model depths, where the structure is controlled by a single local MT site, the correction of static-shift effects leads to vertical scaling of resistivity-thickness products in the model, with the corrected model showing improved correlation to existing borehole wireline resistivity data. In turn, as these vertical scalings are effectively independent of adjacent sites, lateral resistivity distributions are also affected, with up to half a decade of resistivity variation between the models estimated at depths down to 2000 m. Simple estimation of differences in bulk porosity, derived using Archie's Law, between the two models reinforces our conclusion that the suborder of magnitude resistivity contrasts induced by the correction of static shifts correspond to similar contrasts in estimated porosities, and hence, for purposes of reservoir investigation or similar cases requiring accurate absolute resistivity estimates, galvanic distortion correction, especially static-shift correction, is essential.
Wagner, Chad R.; Mueller, David S.
2011-01-01
A negative bias in discharge measurements made with an acoustic Doppler current profiler (ADCP) can be caused by the movement of sediment on or near the streambed. The integration of a global positioning system (GPS) to track the movement of the ADCP can be used to avoid the systematic negative bias associated with a moving streambed. More than 500 discharge transects from 63 discharge measurements with GPS data were collected at sites throughout the US, Canada, and New Zealand with no moving bed to compare GPS and bottom-track-referenced discharges. Although the data indicated some statistical bias depending on site conditions and type of GPS data used, these biases were typically about 0.5% or less. An assessment of differential correction sources was limited by a lack of data collected in a range of different correction sources and different GPS receivers at the same sites. Despite this limitation, the data indicate that the use of Wide Area Augmentation System (WAAS) corrected positional data is acceptable for discharge measurements using GGA as the boat-velocity reference. The discharge data based on GPS-referenced boat velocities from the VTG data string, which does not require differential correction, were comparable to the discharges based on GPS-referenced boat velocities from the differentially-corrected GGA data string. Spatial variability of measure discharges referenced to GGA, VTG and bottom-tracking is higher near the channel banks. The spatial variability of VTG-referenced discharges is correlated with the spatial distribution of maximum Horizontal Dilution of Precision (HDOP) values and the spatial variability of GGA-referenced discharges is correlated with proximity to channel banks.
Measurement Error Correction for Predicted Spatiotemporal Air Pollution Exposures.
Keller, Joshua P; Chang, Howard H; Strickland, Matthew J; Szpiro, Adam A
2017-05-01
Air pollution cohort studies are frequently analyzed in two stages, first modeling exposure then using predicted exposures to estimate health effects in a second regression model. The difference between predicted and unobserved true exposures introduces a form of measurement error in the second stage health model. Recent methods for spatial data correct for measurement error with a bootstrap and by requiring the study design ensure spatial compatibility, that is, monitor and subject locations are drawn from the same spatial distribution. These methods have not previously been applied to spatiotemporal exposure data. We analyzed the association between fine particulate matter (PM2.5) and birth weight in the US state of Georgia using records with estimated date of conception during 2002-2005 (n = 403,881). We predicted trimester-specific PM2.5 exposure using a complex spatiotemporal exposure model. To improve spatial compatibility, we restricted to mothers residing in counties with a PM2.5 monitor (n = 180,440). We accounted for additional measurement error via a nonparametric bootstrap. Third trimester PM2.5 exposure was associated with lower birth weight in the uncorrected (-2.4 g per 1 μg/m difference in exposure; 95% confidence interval [CI]: -3.9, -0.8) and bootstrap-corrected (-2.5 g, 95% CI: -4.2, -0.8) analyses. Results for the unrestricted analysis were attenuated (-0.66 g, 95% CI: -1.7, 0.35). This study presents a novel application of measurement error correction for spatiotemporal air pollution exposures. Our results demonstrate the importance of spatial compatibility between monitor and subject locations and provide evidence of the association between air pollution exposure and birth weight.
Burr, D.M.; Bruno, B.C.; Lanagan, P.D.; Glaze, L.S.; Jaeger, W.L.; Soare, R.J.; Wan, Bun Tseung J.-M.; Skinner, J.A.; Baloga, S.M.
2009-01-01
Fields of mesoscale raised rim depressions (MRRDs) of various origins are found on Earth and Mars. Examples include rootless cones, mud volcanoes, collapsed pingos, rimmed kettle holes, and basaltic ring structures. Correct identification of MRRDs on Mars is valuable because different MRRD types have different geologic and/or climatic implications and are often associated with volcanism and/or water, which may provide locales for biotic or prebiotic activity. In order to facilitate correct identification of fields of MRRDs on Mars and their implications, this work provides a review of common terrestrial MRRD types that occur in fields. In this review, MRRDs by formation mechanism, including hydrovolcanic (phreatomagmatic cones, basaltic ring structures), sedimentological (mud volcanoes), and ice-related (pingos, volatile ice-block forms) mechanisms. For each broad mechanism, we present a comparative synopsis of (i) morphology and observations, (ii) physical formation processes, and (iii) published hypothesized locations on Mars. Because the morphology for MRRDs may be ambiguous, an additional tool is provided for distinguishing fields of MRRDs by origin on Mars, namely, spatial distribution analyses for MRRDs within fields on Earth. We find that MRRDs have both distinguishing and similar characteristics, and observation that applies both to their mesoscale morphology and to their spatial distribution statistics. Thus, this review provides tools for distinguishing between various MRRDs, while highlighting the utility of the multiple working hypotheses approach. ?? 2008 Elsevier Ltd.
Xia, Zhang; Jing-Bo, Xue; He-Hua, Hu; Xiong, Liu; Cai-Xia, Cui; Xiao-Hong, Wen; Xiao-Ping, Xie; Wei-Rong, Zhang; Rong, Tian; Li-Chun, Dong; Chun-Li, Cao; Shi-Zhu, Li; Yi-Biao, Zhou
2017-03-07
To understand the spatial distribution characteristics of wild feces in schistosomiasis endemic areas of Jiangling County, Hubei Province and further explore the source of infection efficiently, so as to provide the evidence for the development of corresponding monitoring and response technology. In 2011, the fresh wild feces were investigated every two months in the selected 15 villages by the severity of historical endemic in Jiangling County. The schistosome miracidium hatching method was used to test the schistosome infection of the wild feces. The descriptive analysis and spatial analysis were used for the description of the spatial distribution of the wild feces. Totally 701 wild feces samples were collected with the average density of 0.055 6/100 m 2 , and the positive rate of the wild feces was 11.70% (82/701). The results of the regression analysis showed a positive spatial correlation between the positive rate of wild feces and the rate of human infection, the area with infected Oncomelania hupensis and the number of fenced cattle, and the corrected R 2 of the model was 0.58. The infection rate of wild feces is positively correlated with the rate of human infection, area with infected O. hupensis and number of fenced cattle in space in Jiangling County, so the prevention and control measures could be conducted according to the spatial distribution of the positive wild feces.
Monitoring Method of Cow Anthrax Based on Gis and Spatial Statistical Analysis
NASA Astrophysics Data System (ADS)
Li, Lin; Yang, Yong; Wang, Hongbin; Dong, Jing; Zhao, Yujun; He, Jianbin; Fan, Honggang
Geographic information system (GIS) is a computer application system, which possesses the ability of manipulating spatial information and has been used in many fields related with the spatial information management. Many methods and models have been established for analyzing animal diseases distribution models and temporal-spatial transmission models. Great benefits have been gained from the application of GIS in animal disease epidemiology. GIS is now a very important tool in animal disease epidemiological research. Spatial analysis function of GIS can be widened and strengthened by using spatial statistical analysis, allowing for the deeper exploration, analysis, manipulation and interpretation of spatial pattern and spatial correlation of the animal disease. In this paper, we analyzed the cow anthrax spatial distribution characteristics in the target district A (due to the secret of epidemic data we call it district A) based on the established GIS of the cow anthrax in this district in combination of spatial statistical analysis and GIS. The Cow anthrax is biogeochemical disease, and its geographical distribution is related closely to the environmental factors of habitats and has some spatial characteristics, and therefore the correct analysis of the spatial distribution of anthrax cow for monitoring and the prevention and control of anthrax has a very important role. However, the application of classic statistical methods in some areas is very difficult because of the pastoral nomadic context. The high mobility of livestock and the lack of enough suitable sampling for the some of the difficulties in monitoring currently make it nearly impossible to apply rigorous random sampling methods. It is thus necessary to develop an alternative sampling method, which could overcome the lack of sampling and meet the requirements for randomness. The GIS computer application software ArcGIS9.1 was used to overcome the lack of data of sampling sites.Using ArcGIS 9.1 and GEODA to analyze the cow anthrax spatial distribution of district A. we gained some conclusions about cow anthrax' density: (1) there is a spatial clustering model. (2) there is an intensely spatial autocorrelation. We established a prediction model to estimate the anthrax distribution based on the spatial characteristic of the density of cow anthrax. Comparing with the true distribution, the prediction model has a well coincidence and is feasible to the application. The method using a GIS tool facilitates can be implemented significantly in the cow anthrax monitoring and investigation, and the space statistics - related prediction model provides a fundamental use for other study on space-related animal diseases.
Automated processing for proton spectroscopic imaging using water reference deconvolution.
Maudsley, A A; Wu, Z; Meyerhoff, D J; Weiner, M W
1994-06-01
Automated formation of MR spectroscopic images (MRSI) is necessary before routine application of these methods is possible for in vivo studies; however, this task is complicated by the presence of spatially dependent instrumental distortions and the complex nature of the MR spectrum. A data processing method is presented for completely automated formation of in vivo proton spectroscopic images, and applied for analysis of human brain metabolites. This procedure uses the water reference deconvolution method (G. A. Morris, J. Magn. Reson. 80, 547(1988)) to correct for line shape distortions caused by instrumental and sample characteristics, followed by parametric spectral analysis. Results for automated image formation were found to compare favorably with operator dependent spectral integration methods. While the water reference deconvolution processing was found to provide good correction of spatially dependent resonance frequency shifts, it was found to be susceptible to errors for correction of line shape distortions. These occur due to differences between the water reference and the metabolite distributions.
NASA Astrophysics Data System (ADS)
Donaldson, Lloyd; Vaidya, Alankar
2017-03-01
Mapping the location of bound cellulase enzymes provides information on the micro-scale distribution of amenable and recalcitrant sites in pretreated woody biomass for biofuel applications. The interaction of a fluorescently labelled cellulase enzyme cocktail with steam-exploded pine (SEW) was quantified using confocal microscopy. The spatial distribution of Dylight labelled cellulase was quantified relative to lignin (autofluorescence) and cellulose (Congo red staining) by measuring their colocalisation using Pearson correlations. Correlations were greater in cellulose-rich secondary cell walls compared to lignin-rich middle lamella but with significant variations among individual biomass particles. The distribution of cellulose in the pretreated biomass accounted for 30% of the variation in the distribution of enzyme after correcting for the correlation between lignin and cellulose. For the first time, colocalisation analysis was able to quantify the spatial distribution of amenable and recalcitrant sites in relation to the histochemistry of cellulose and lignin. This study will contribute to understanding the role of pretreatment in enzymatic hydrolysis of recalcitrant softwood biomass.
NASA Astrophysics Data System (ADS)
Frey, M. P.; Stamm, C.; Schneider, M. K.; Reichert, P.
2011-12-01
A distributed hydrological model was used to simulate the distribution of fast runoff formation as a proxy for critical source areas for herbicide pollution in a small agricultural catchment in Switzerland. We tested to what degree predictions based on prior knowledge without local measurements could be improved upon relying on observed discharge. This learning process consisted of five steps: For the prior prediction (step 1), knowledge of the model parameters was coarse and predictions were fairly uncertain. In the second step, discharge data were used to update the prior parameter distribution. Effects of uncertainty in input data and model structure were accounted for by an autoregressive error model. This step decreased the width of the marginal distributions of parameters describing the lower boundary (percolation rates) but hardly affected soil hydraulic parameters. Residual analysis (step 3) revealed model structure deficits. We modified the model, and in the subsequent Bayesian updating (step 4) the widths of the posterior marginal distributions were reduced for most parameters compared to those of the prior. This incremental procedure led to a strong reduction in the uncertainty of the spatial prediction. Thus, despite only using spatially integrated data (discharge), the spatially distributed effect of the improved model structure can be expected to improve the spatially distributed predictions also. The fifth step consisted of a test with independent spatial data on herbicide losses and revealed ambiguous results. The comparison depended critically on the ratio of event to preevent water that was discharged. This ratio cannot be estimated from hydrological data only. The results demonstrate that the value of local data is strongly dependent on a correct model structure. An iterative procedure of Bayesian updating, model testing, and model modification is suggested.
Cross, Russell; Olivieri, Laura; O'Brien, Kendall; Kellman, Peter; Xue, Hui; Hansen, Michael
2016-02-25
Traditional cine imaging for cardiac functional assessment requires breath-holding, which can be problematic in some situations. Free-breathing techniques have relied on multiple averages or real-time imaging, producing images that can be spatially and/or temporally blurred. To overcome this, methods have been developed to acquire real-time images over multiple cardiac cycles, which are subsequently motion corrected and reformatted to yield a single image series displaying one cardiac cycle with high temporal and spatial resolution. Application of these algorithms has required significant additional reconstruction time. The use of distributed computing was recently proposed as a way to improve clinical workflow with such algorithms. In this study, we have deployed a distributed computing version of motion corrected re-binning reconstruction for free-breathing evaluation of cardiac function. Twenty five patients and 25 volunteers underwent cardiovascular magnetic resonance (CMR) for evaluation of left ventricular end-systolic volume (ESV), end-diastolic volume (EDV), and end-diastolic mass. Measurements using motion corrected re-binning were compared to those using breath-held SSFP and to free-breathing SSFP with multiple averages, and were performed by two independent observers. Pearson correlation coefficients and Bland-Altman plots tested agreement across techniques. Concordance correlation coefficient and Bland-Altman analysis tested inter-observer variability. Total scan plus reconstruction times were tested for significant differences using paired t-test. Measured volumes and mass obtained by motion corrected re-binning and by averaged free-breathing SSFP compared favorably to those obtained by breath-held SSFP (r = 0.9863/0.9813 for EDV, 0.9550/0.9685 for ESV, 0.9952/0.9771 for mass). Inter-observer variability was good with concordance correlation coefficients between observers across all acquisition types suggesting substantial agreement. Both motion corrected re-binning and averaged free-breathing SSFP acquisition and reconstruction times were shorter than breath-held SSFP techniques (p < 0.0001). On average, motion corrected re-binning required 3 min less than breath-held SSFP imaging, a 37% reduction in acquisition and reconstruction time. The motion corrected re-binning image reconstruction technique provides robust cardiac imaging that can be used for quantification that compares favorably to breath-held SSFP as well as multiple average free-breathing SSFP, but can be obtained in a fraction of the time when using cloud-based distributed computing reconstruction.
Linard, Catherine; Lamarque, Pénélope; Heyman, Paul; Ducoffre, Geneviève; Luyasu, Victor; Tersago, Katrien; Vanwambeke, Sophie O; Lambin, Eric F
2007-01-01
Background Vector-borne and zoonotic diseases generally display clear spatial patterns due to different space-dependent factors. Land cover and land use influence disease transmission by controlling both the spatial distribution of vectors or hosts, and the probability of contact with susceptible human populations. The objective of this study was to combine environmental and socio-economic factors to explain the spatial distribution of two emerging human diseases in Belgium, Puumala virus (PUUV) and Lyme borreliosis. Municipalities were taken as units of analysis. Results Negative binomial regressions including a correction for spatial endogeneity show that the spatial distribution of PUUV and Lyme borreliosis infections are associated with a combination of factors linked to the vector and host populations, to human behaviours, and to landscape attributes. Both diseases are associated with the presence of forests, which are the preferred habitat for vector or host populations. The PUUV infection risk is higher in remote forest areas, where the level of urbanisation is low, and among low-income populations. The Lyme borreliosis transmission risk is higher in mixed landscapes with forests and spatially dispersed houses, mostly in wealthy peri-urban areas. The spatial dependence resulting from a combination of endogenous and exogenous processes could be accounted for in the model on PUUV but not for Lyme borreliosis. Conclusion A large part of the spatial variation in disease risk can be explained by environmental and socio-economic factors. The two diseases not only are most prevalent in different regions but also affect different groups of people. Combining these two criteria may increase the efficiency of information campaigns through appropriate targeting. PMID:17474974
Farias, Paulo R S; Barbosa, José C; Busoli, Antonio C; Overal, William L; Miranda, Vicente S; Ribeiro, Susane M
2008-01-01
The fall armyworm, Spodoptera frugiperda (J.E. Smith), is one of the chief pests of maize in the Americas. The study of its spatial distribution is fundamental for designing correct control strategies, improving sampling methods, determining actual and potential crop losses, and adopting precise agricultural techniques. In São Paulo state, Brazil, a maize field was sampled at weekly intervals, from germination through harvest, for caterpillar densities, using quadrates. In each of 200 quadrates, 10 plants were sampled per week. Harvest weights were obtained in the field for each quadrate, and ear diameters and lengths were also sampled (15 ears per quadrate) and used to estimate potential productivity of the quadrate. Geostatistical analyses of caterpillar densities showed greatest ranges for small caterpillars when semivariograms were adjusted for a spherical model that showed greatest fit. As the caterpillars developed in the field, their spatial distribution became increasingly random, as shown by a model adjusted to a straight line, indicating a lack of spatial dependence among samples. Harvest weight and ear length followed the spherical model, indicating the existence of spatial variability of the production parameters in the maize field. Geostatistics shows promise for the application of precise methods in the integrated control of pests.
NASA Astrophysics Data System (ADS)
Bliss, Donald; Franzoni, Linda; Rouse, Jerry; Manning, Ben
2005-09-01
An analysis method for time-dependent broadband diffuse sound fields in enclosures is described. Beginning with a formulation utilizing time-dependent broadband intensity boundary sources, the strength of these wall sources is expanded in a series in powers of an absorption parameter, thereby giving a separate boundary integral problem for each power. The temporal behavior is characterized by a Taylor expansion in the delay time for a source to influence an evaluation point. The lowest-order problem has a uniform interior field proportional to the reciprocal of the absorption parameter, as expected, and exhibits relatively slow exponential decay. The next-order problem gives a mean-square pressure distribution that is independent of the absorption parameter and is primarily responsible for the spatial variation of the reverberant field. This problem, which is driven by input sources and the lowest-order reverberant field, depends on source location and the spatial distribution of absorption. Additional problems proceed at integer powers of the absorption parameter, but are essentially higher-order corrections to the spatial variation. Temporal behavior is expressed in terms of an eigenvalue problem, with boundary source strength distributions expressed as eigenmodes. Solutions exhibit rapid short-time spatial redistribution followed by long-time decay of a predominant spatial mode.
Spatial analysis to identify hotspots of prevalence of schizophrenia.
Moreno, Berta; García-Alonso, Carlos R; Negrín Hernández, Miguel A; Torres-González, Francisco; Salvador-Carulla, Luis
2008-10-01
The geographical distribution of mental health disorders is useful information for epidemiological research and health services planning. To determine the existence of geographical hotspots with a high prevalence of schizophrenia in a mental health area in Spain. The study included 774 patients with schizophrenia who were users of the community mental health care service in the area of South Granada. Spatial analysis (Kernel estimation) and Bayesian relative risks were used to locate potential hotspots. Availability and accessibility were both rated in each zone and spatial algebra was applied to identify hotspots in a particular zone. The age-corrected prevalence rate of schizophrenia was 2.86 per 1,000 population in the South Granada area. Bayesian analysis showed a relative risk varying from 0.43 to 2.33. The area analysed had a non-uniform spatial distribution of schizophrenia, with one main hotspot (zone S2). This zone had poor accessibility to and availability of mental health services. A municipality-based variation exists in the prevalence of schizophrenia and related disorders in the study area. Spatial analysis techniques are useful tools to analyse the heterogeneous distribution of a variable and to explain genetic/environmental factors in hotspots related with a lack of easy availability of and accessibility to adequate health care services.
A new phase correction method in NMR imaging based on autocorrelation and histogram analysis.
Ahn, C B; Cho, Z H
1987-01-01
A new statistical approach to phase correction in NMR imaging is proposed. The proposed scheme consists of first-and zero-order phase corrections each by the inverse multiplication of estimated phase error. The first-order error is estimated by the phase of autocorrelation calculated from the complex valued phase distorted image while the zero-order correction factor is extracted from the histogram of phase distribution of the first-order corrected image. Since all the correction procedures are performed on the spatial domain after completion of data acquisition, no prior adjustments or additional measurements are required. The algorithm can be applicable to most of the phase-involved NMR imaging techniques including inversion recovery imaging, quadrature modulated imaging, spectroscopic imaging, and flow imaging, etc. Some experimental results with inversion recovery imaging as well as quadrature spectroscopic imaging are shown to demonstrate the usefulness of the algorithm.
ICESat laser altimetry over small mountain glaciers
NASA Astrophysics Data System (ADS)
Treichler, Désirée; Kääb, Andreas
2016-09-01
Using sparsely glaciated southern Norway as a case study, we assess the potential and limitations of ICESat laser altimetry for analysing regional glacier elevation change in rough mountain terrain. Differences between ICESat GLAS elevations and reference elevation data are plotted over time to derive a glacier surface elevation trend for the ICESat acquisition period 2003-2008. We find spatially varying biases between ICESat and three tested digital elevation models (DEMs): the Norwegian national DEM, SRTM DEM, and a high-resolution lidar DEM. For regional glacier elevation change, the spatial inconsistency of reference DEMs - a result of spatio-temporal merging - has the potential to significantly affect or dilute trends. Elevation uncertainties of all three tested DEMs exceed ICESat elevation uncertainty by an order of magnitude, and are thus limiting the accuracy of the method, rather than ICESat uncertainty. ICESat matches glacier size distribution of the study area well and measures small ice patches not commonly monitored in situ. The sample is large enough for spatial and thematic subsetting. Vertical offsets to ICESat elevations vary for different glaciers in southern Norway due to spatially inconsistent reference DEM age. We introduce a per-glacier correction that removes these spatially varying offsets, and considerably increases trend significance. Only after application of this correction do individual campaigns fit observed in situ glacier mass balance. Our correction also has the potential to improve glacier trend significance for other causes of spatially varying vertical offsets, for instance due to radar penetration into ice and snow for the SRTM DEM or as a consequence of mosaicking and merging that is common for national or global DEMs. After correction of reference elevation bias, we find that ICESat provides a robust and realistic estimate of a moderately negative glacier mass balance of around -0.36 ± 0.07 m ice per year. This regional estimate agrees well with the heterogeneous but overall negative in situ glacier mass balance observed in the area.
Optimizing the Hydrological and Biogeochemical Simulations on a Hillslope with Stony Soil
NASA Astrophysics Data System (ADS)
Zhu, Q.
2017-12-01
Stony soils are widely distributed in the hilly area. However, traditional pedotransfer functions are not reliable in predicting the soil hydraulic parameters for these soils due to the impacts of rock fragments. Therefore, large uncertainties and errors may exist in the hillslope hydrological and biogeochemical simulations in stony soils due to poor estimations of soil hydraulic parameters. In addition, homogenous soil hydraulic parameters are usually used in traditional hillslope simulations. However, soil hydraulic parameters are spatially heterogeneous on the hillslope. This may also cause the unreliable simulations. In this study, we obtained soil hydraulic parameters using five different approaches on a tea hillslope in Taihu Lake basin, China. These five approaches included (1) Rossetta predicted and spatially homogenous, (2) Rossetta predicted and spatially heterogeneous), (3) Rossetta predicted, rock fragment corrected and spatially homogenous, (4) Rossetta predicted, rock fragment corrected and spatially heterogeneous, and (5) extracted from observed soil-water retention curves fitted by dual-pore function and spatially heterogeneous (observed). These five sets of soil hydraulic properties were then input into Hydrus-3D and DNDC to simulate the soil hydrological and biogeochemical processes. The aim of this study is testing two hypotheses. First, considering the spatial heterogeneity of soil hydraulic parameters will improve the simulations. Second, considering the impact of rock fragment on soil hydraulic parameters will improve the simulations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Yokogawa, D., E-mail: d.yokogawa@chem.nagoya-u.ac.jp; Institute of Transformative Bio-Molecules
2016-09-07
Theoretical approach to design bright bio-imaging molecules is one of the most progressing ones. However, because of the system size and computational accuracy, the number of theoretical studies is limited to our knowledge. To overcome the difficulties, we developed a new method based on reference interaction site model self-consistent field explicitly including spatial electron density distribution and time-dependent density functional theory. We applied it to the calculation of indole and 5-cyanoindole at ground and excited states in gas and solution phases. The changes in the optimized geometries were clearly explained with resonance structures and the Stokes shift was correctly reproduced.
Faure, Florian; Saini, Camille; Potter, Gaël; Galgani, François; de Alencastro, Luiz Felippe; Hagmann, Pascal
2015-08-01
This study examines the distribution, abundance and characteristics of surface micro- and mesoplastic debris in the Western Mediterranean Sea. 41 samples were collected in 2011 (summer) and 2012 (summer). Results, firstly, revealed that micro- (<5 mm) and mesoplastic debris were widely and uniformly distributed in this area with average concentrations of 130,000 parts/km(2) and 5700 parts/km(2), respectively. Importantly, a strong correlation between micro- and mesoplastic concentrations was identified. Secondly, a classification based on the shape and appearance of microplastics indicated the predominant presence of fragments (73%) followed by thin films (14%). Thirdly, the average mass ratio of microplastic to dry organic matter has been measured at 0.5, revealing a significant presence of microplastics in comparison to plankton. Finally, a correction method was applied in order to correct wind mixing effect on microplastics' vertical distribution. This data allows for a comprehensive view, for the first time, of the spatial distribution and nature of plastic debris in the Western Mediterranean Sea.
NASA Astrophysics Data System (ADS)
Abitew, T. A.; van Griensven, A.; Bauwens, W.
2015-12-01
Evapotranspiration is the main process in hydrology (on average around 60%), though has not received as much attention in the evaluation and calibration of hydrological models. In this study, Remote Sensing (RS) derived Evapotranspiration (ET) is used to improve the spatially distributed processes of ET of SWAT model application in the upper Mara basin (Kenya) and the Blue Nile basin (Ethiopia). The RS derived ET data is obtained from recently compiled global datasets (continuously monthly data at 1 km resolution from MOD16NBI,SSEBop,ALEXI,CMRSET models) and from regionally applied Energy Balance Models (for several cloud free days). The RS-RT data is used in different forms: Method 1) to evaluate spatially distributed evapotransiration model resultsMethod 2) to calibrate the evotranspiration processes in hydrological modelMethod 3) to bias-correct the evapotranpiration in hydrological model during simulation after changing the SWAT codesAn inter-comparison of the RS-ET products shows that at present there is a significant bias, but at the same time an agreement on the spatial variability of ET. The ensemble mean of different ET products seems the most realistic estimation and was further used in this study.The results show that:Method 1) the spatially mapped evapotranspiration of hydrological models shows clear differences when compared to RS derived evapotranspiration (low correlations). Especially evapotranspiration in forested areas is strongly underestimated compared to other land covers.Method 2) Calibration allows to improve the correlations between the RS and hydrological model results to some extent.Method 3) Bias-corrections are efficient in producing (sesonal or annual) evapotranspiration maps from hydrological models which are very similar to the patterns obtained from RS data.Though the bias-correction is very efficient, it is advised to improve the model results by better representing the ET processes by improved plant/crop computations, improved agricultural management practices or by providing improved meteorological data.
USDA-ARS?s Scientific Manuscript database
Accurately predicting phenology in crop simulation models is critical for correctly simulating crop production. While extensive work in modeling phenology has focused on the temperature response function (resulting in robust phenology models), limited work on quantifying the phenological responses t...
Cohen, Michael X
2015-09-01
The purpose of this paper is to compare the effects of different spatial transformations applied to the same scalp-recorded EEG data. The spatial transformations applied are two referencing schemes (average and linked earlobes), the surface Laplacian, and beamforming (a distributed source localization procedure). EEG data were collected during a speeded reaction time task that provided a comparison of activity between error vs. correct responses. Analyses focused on time-frequency power, frequency band-specific inter-electrode connectivity, and within-subject cross-trial correlations between EEG activity and reaction time. Time-frequency power analyses showed similar patterns of midfrontal delta-theta power for errors compared to correct responses across all spatial transformations. Beamforming additionally revealed error-related anterior and lateral prefrontal beta-band activity. Within-subject brain-behavior correlations showed similar patterns of results across the spatial transformations, with the correlations being the weakest after beamforming. The most striking difference among the spatial transformations was seen in connectivity analyses: linked earlobe reference produced weak inter-site connectivity that was attributable to volume conduction (zero phase lag), while the average reference and Laplacian produced more interpretable connectivity results. Beamforming did not reveal any significant condition modulations of connectivity. Overall, these analyses show that some findings are robust to spatial transformations, while other findings, particularly those involving cross-trial analyses or connectivity, are more sensitive and may depend on the use of appropriate spatial transformations. Copyright © 2014 Elsevier B.V. All rights reserved.
Fast determination of the spatially distributed photon fluence for light dose evaluation of PDT
NASA Astrophysics Data System (ADS)
Zhao, Kuanxin; Chen, Weiting; Li, Tongxin; Yan, Panpan; Qin, Zhuanping; Zhao, Huijuan
2018-02-01
Photodynamic therapy (PDT) has shown superiorities of noninvasiveness and high-efficiency in the treatment of early-stage skin cancer. Rapid and accurate determination of spatially distributed photon fluence in turbid tissue is essential for the dosimetry evaluation of PDT. It is generally known that photon fluence can be accurately obtained by Monte Carlo (MC) methods, while too much time would be consumed especially for complex light source mode or online real-time dosimetry evaluation of PDT. In this work, a method to rapidly calculate spatially distributed photon fluence in turbid medium is proposed implementing a classical perturbation and iteration theory on mesh Monte Carlo (MMC). In the proposed method, photon fluence can be obtained by superposing a perturbed and iterative solution caused by the defects in turbid medium to an unperturbed solution for the background medium and therefore repetitive MMC simulations can be avoided. To validate the method, a non-melanoma skin cancer model is carried out. The simulation results show the solution of photon fluence can be obtained quickly and correctly by perturbation algorithm.
Thermal equilibrium and statistical thermometers in special relativity.
Cubero, David; Casado-Pascual, Jesús; Dunkel, Jörn; Talkner, Peter; Hänggi, Peter
2007-10-26
There is an intense debate in the recent literature about the correct generalization of Maxwell's velocity distribution in special relativity. The most frequently discussed candidate distributions include the Jüttner function as well as modifications thereof. Here we report results from fully relativistic one-dimensional molecular dynamics simulations that resolve the ambiguity. The numerical evidence unequivocally favors the Jüttner distribution. Moreover, our simulations illustrate that the concept of "thermal equilibrium" extends naturally to special relativity only if a many-particle system is spatially confined. They make evident that "temperature" can be statistically defined and measured in an observer frame independent way.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Pacilio, Massimiliano, E-mail: mpacilio@scamillofo
Purpose: Many centers aim to plan liver transarterial radioembolization (TARE) with dosimetry, even without CT-based attenuation correction (AC), or with unoptimized scatter correction (SC) methods. This work investigates the impact of presence vs absence of such corrections, and limited spatial resolution, on 3D dosimetry for TARE. Methods: Three voxelized phantoms were derived from CT images of real patients with different body sizes. Simulations of {sup 99m}Tc-SPECT projections were performed with the SIMIND code, assuming three activity distributions in the liver: uniform, inside a “liver’s segment,” or distributing multiple uptaking nodules (“nonuniform liver”), with a tumoral liver/healthy parenchyma ratio of 5:1.more » Projection data were reconstructed by a commercial workstation, with OSEM protocol not specifically optimized for dosimetry (spatial resolution of 12.6 mm), with/without SC (optimized, or with parameters predefined by the manufacturer; dual energy window), and with/without AC. Activity in voxels was calculated by a relative calibration, assuming identical microspheres and {sup 99m}Tc-SPECT counts spatial distribution. 3D dose distributions were calculated by convolution with {sup 90}Y voxel S-values, assuming permanent trapping of microspheres. Cumulative dose-volume histograms in lesions and healthy parenchyma from different reconstructions were compared with those obtained from the reference biodistribution (the “gold standard,” GS), assessing differences for D95%, D70%, and D50% (i.e., minimum value of the absorbed dose to a percentage of the irradiated volume). γ tool analysis with tolerance of 3%/13 mm was used to evaluate the agreement between GS and simulated cases. The influence of deep-breathing was studied, blurring the reference biodistributions with a 3D anisotropic gaussian kernel, and performing the simulations once again. Results: Differences of the dosimetric indicators were noticeable in some cases, always negative for lesions and distributed around zero for parenchyma. Application of AC and SC reduced systematically the differences for lesions by 5%–14% for a liver segment, and by 7%–12% for a nonuniform liver. For parenchyma, the data trend was less clear, but the overall range of variability passed from −10%/40% for a liver segment, and −10%/20% for a nonuniform liver, to −13%/6% in both cases. Applying AC, SC with preset parameters gave similar results to optimized SC, as confirmed by γ tool analysis. Moreover, γ analysis confirmed that solely AC and SC are not sufficient to obtain accurate 3D dose distribution. With breathing, the accuracy worsened severely for all dosimetric indicators, above all for lesions: with AC and optimized SC, −38%/−13% in liver’s segment, −61%/−40% in the nonuniform liver. For parenchyma, D50% resulted always less sensitive to breathing and sub-optimal correction methods (difference overall range: −7%/13%). Conclusions: Reconstruction protocol optimization, AC, SC, PVE and respiratory motion corrections should be implemented to obtain the best possible dosimetric accuracy. On the other side, thanks to the relative calibration, D50% inaccuracy for the healthy parenchyma from absence of AC was less than expected, while the optimization of SC was scarcely influent. The relative calibration therefore allows to perform TARE planning, basing on D50% for the healthy parenchyma, even without AC or with suboptimal corrections, rather than rely on nondosimetric methods.« less
Assessing the Added Value of Dynamical Downscaling in the Context of Hydrologic Implication
NASA Astrophysics Data System (ADS)
Lu, M.; IM, E. S.; Lee, M. H.
2017-12-01
There is a scientific consensus that high-resolution climate simulations downscaled by Regional Climate Models (RCMs) can provide valuable refined information over the target region. However, a significant body of hydrologic impact assessment has been performing using the climate information provided by Global Climate Models (GCMs) in spite of a fundamental spatial scale gap. It is probably based on the assumption that the substantial biases and spatial scale gap from GCMs raw data can be simply removed by applying the statistical bias correction and spatial disaggregation. Indeed, many previous studies argue that the benefit of dynamical downscaling using RCMs is minimal when linking climate data with the hydrological model, from the comparison of the impact between bias-corrected GCMs and bias-corrected RCMs on hydrologic simulations. It may be true for long-term averaged climatological pattern, but it is not necessarily the case when looking into variability across various temporal spectrum. In this study, we investigate the added value of dynamical downscaling focusing on the performance in capturing climate variability. For doing this, we evaluate the performance of the distributed hydrological model over the Korean river basin using the raw output from GCM and RCM, and bias-corrected output from GCM and RCM. The impacts of climate input data on streamflow simulation are comprehensively analyzed. [Acknowledgements]This research is supported by the Korea Agency for Infrastructure Technology Advancement (KAIA) grant funded by the Ministry of Land, Infrastructure and Transport (Grant 17AWMP-B083066-04).
Inhomogeneity Based Characterization of Distribution Patterns on the Plasma Membrane
Paparelli, Laura; Corthout, Nikky; Wakefield, Devin L.; Sannerud, Ragna; Jovanovic-Talisman, Tijana; Annaert, Wim; Munck, Sebastian
2016-01-01
Cell surface protein and lipid molecules are organized in various patterns: randomly, along gradients, or clustered when segregated into discrete micro- and nano-domains. Their distribution is tightly coupled to events such as polarization, endocytosis, and intracellular signaling, but challenging to quantify using traditional techniques. Here we present a novel approach to quantify the distribution of plasma membrane proteins and lipids. This approach describes spatial patterns in degrees of inhomogeneity and incorporates an intensity-based correction to analyze images with a wide range of resolutions; we have termed it Quantitative Analysis of the Spatial distributions in Images using Mosaic segmentation and Dual parameter Optimization in Histograms (QuASIMoDOH). We tested its applicability using simulated microscopy images and images acquired by widefield microscopy, total internal reflection microscopy, structured illumination microscopy, and photoactivated localization microscopy. We validated QuASIMoDOH, successfully quantifying the distribution of protein and lipid molecules detected with several labeling techniques, in different cell model systems. We also used this method to characterize the reorganization of cell surface lipids in response to disrupted endosomal trafficking and to detect dynamic changes in the global and local organization of epidermal growth factor receptors across the cell surface. Our findings demonstrate that QuASIMoDOH can be used to assess protein and lipid patterns, quantifying distribution changes and spatial reorganization at the cell surface. An ImageJ/Fiji plugin of this analysis tool is provided. PMID:27603951
The impact of runoff generation mechanisms on the location of critical source areas
Lyon, S.W.; McHale, M.R.; Walter, M.T.; Steenhuis, T.S.
2006-01-01
Identifying phosphorus (P) source areas and transport pathways is a key step in decreasing P loading to natural water systems. This study compared the effects of two modeled runoff generation processes - saturation excess and infiltration excess - on total phosphorus (TP) and soluble reactive phosphorus (SRP) concentrations in 10 catchment streams of a Catskill mountain watershed in southeastern New York. The spatial distribution of runoff from forested land and agricultural land was generated for both runoff processes; results of both distributions were consistent with Soil Conservation Service-Curve Number (SCS-CN) theory. These spatial runoff distributions were then used to simulate stream concentrations of TP and SRP through a simple equation derived from an observed relation between P concentration and land use; empirical results indicate that TP and SRP concentrations increased with increasing percentage of agricultural land. Simulated TP and SRP stream concentrations predicted for the 10 catchments were strongly affected by the assumed runoff mechanism. The modeled TP and SRP concentrations produced by saturation excess distribution averaged 31 percent higher and 42 percent higher, respectively, than those produced by the infiltration excess distribution. Misrepresenting the primary runoff mechanism could not only produce erroneous concentrations, it could fail to correctly locate critical source areas for implementation of best management practices. Thus, identification of the primary runoff mechanism is critical in selection of appropriate models in the mitigation of nonpoint source pollution. Correct representation of runoff processes is also critical in the future development of biogeochemical transport models, especially those that address nutrient fluxes.
Konz, Ioana; Fernández, Beatriz; Fernández, M Luisa; Pereiro, Rosario; González, Héctor; Alvarez, Lydia; Coca-Prados, Miguel; Sanz-Medel, Alfredo
2013-04-01
Laser ablation coupled to inductively coupled plasma mass spectrometry has been developed for the elemental imaging of Mg, Fe and Cu distribution in histological tissue sections of fixed eyes, embedded in paraffin, from human donors (cadavers). This work presents the development of a novel internal standard correction methodology based on the deposition of a homogeneous thin gold film on the tissue surface and the use of the (197)Au(+) signal as internal standard. Sample preparation (tissue section thickness) and laser conditions were carefully optimized, and internal normalisation using (197)Au(+) was compared with (13)C(+) correction for imaging applications. (24)Mg(+), (56)Fe(+) and (63)Cu(+) distributions were investigated in histological sections of the anterior segment of the eye (including the iris, ciliary body, cornea and trabecular meshwork) and were shown to be heterogeneously distributed along those tissue structures. Reproducibility was assessed by imaging different human eye sections from the same donor and from ten different eyes from adult normal donors, which showed that similar spatial maps were obtained and therefore demonstrate the analytical potential of using (197)Au(+) as internal standard. The proposed analytical approach could offer a robust tool with great practical interest for clinical studies, e.g. to investigate trace element distribution of metals and their alterations in ocular diseases.
Gopinath, Kaundinya; Krishnamurthy, Venkatagiri; Lacey, Simon; Sathian, K
2018-02-01
In a recent study Eklund et al. have shown that cluster-wise family-wise error (FWE) rate-corrected inferences made in parametric statistical method-based functional magnetic resonance imaging (fMRI) studies over the past couple of decades may have been invalid, particularly for cluster defining thresholds less stringent than p < 0.001; principally because the spatial autocorrelation functions (sACFs) of fMRI data had been modeled incorrectly to follow a Gaussian form, whereas empirical data suggest otherwise. Hence, the residuals from general linear model (GLM)-based fMRI activation estimates in these studies may not have possessed a homogenously Gaussian sACF. Here we propose a method based on the assumption that heterogeneity and non-Gaussianity of the sACF of the first-level GLM analysis residuals, as well as temporal autocorrelations in the first-level voxel residual time-series, are caused by unmodeled MRI signal from neuronal and physiological processes as well as motion and other artifacts, which can be approximated by appropriate decompositions of the first-level residuals with principal component analysis (PCA), and removed. We show that application of this method yields GLM residuals with significantly reduced spatial correlation, nearly Gaussian sACF and uniform spatial smoothness across the brain, thereby allowing valid cluster-based FWE-corrected inferences based on assumption of Gaussian spatial noise. We further show that application of this method renders the voxel time-series of first-level GLM residuals independent, and identically distributed across time (which is a necessary condition for appropriate voxel-level GLM inference), without having to fit ad hoc stochastic colored noise models. Furthermore, the detection power of individual subject brain activation analysis is enhanced. This method will be especially useful for case studies, which rely on first-level GLM analysis inferences.
Heers, Marcel; Chowdhury, Rasheda A; Hedrich, Tanguy; Dubeau, François; Hall, Jeffery A; Lina, Jean-Marc; Grova, Christophe; Kobayashi, Eliane
2016-01-01
Distributed inverse solutions aim to realistically reconstruct the origin of interictal epileptic discharges (IEDs) from noninvasively recorded electroencephalography (EEG) and magnetoencephalography (MEG) signals. Our aim was to compare the performance of different distributed inverse solutions in localizing IEDs: coherent maximum entropy on the mean (cMEM), hierarchical Bayesian implementations of independent identically distributed sources (IID, minimum norm prior) and spatially coherent sources (COH, spatial smoothness prior). Source maxima (i.e., the vertex with the maximum source amplitude) of IEDs in 14 EEG and 19 MEG studies from 15 patients with focal epilepsy were analyzed. We visually compared their concordance with intracranial EEG (iEEG) based on 17 cortical regions of interest and their spatial dispersion around source maxima. Magnetic source imaging (MSI) maxima from cMEM were most often confirmed by iEEG (cMEM: 14/19, COH: 9/19, IID: 8/19 studies). COH electric source imaging (ESI) maxima co-localized best with iEEG (cMEM: 8/14, COH: 11/14, IID: 10/14 studies). In addition, cMEM was less spatially spread than COH and IID for ESI and MSI (p < 0.001 Bonferroni-corrected post hoc t test). Highest positive predictive values for cortical regions with IEDs in iEEG could be obtained with cMEM for MSI and with COH for ESI. Additional realistic EEG/MEG simulations confirmed our findings. Accurate spatially extended sources, as found in cMEM (ESI and MSI) and COH (ESI) are desirable for source imaging of IEDs because this might influence surgical decision. Our simulations suggest that COH and IID overestimate the spatial extent of the generators compared to cMEM.
A merged surface reflectance product from the Landsat and Sentinel-2 Missions
NASA Astrophysics Data System (ADS)
Vermote, E.; Claverie, M.; Masek, J. G.; Becker-Reshef, I.; Justice, C. O.
2013-12-01
This project is aimed at producing a merged surface product from the Landsat and Sentinel-2 missions to ultimately achieve high temporal coverage (~2 days repeat cycle) at high spatial resolution (20-60m). The goal is to achieve a seamless/consistent stream of surface reflectance data from the different sensors. The first part of this presentation discusses the basic requirements of such a product and the necessary processing steps: mainly calibration, atmospheric corrections, BRDF effect corrections, spectral band pass adjustments and gridding. We demonstrate the performance of those different corrections by using MODIS and VIIRS (Climate Modeling Grid at 0.05deg) data globally as well as Formosat-2 (8m spatial resolution) data (one crop site in South of France where 105 scenes were acquired during 2006-2010). The consistency of the surface reflectance product from MODIS and Formosat-2 ranges from 6 to 8% relative depending on the spectral bands (Green to NIR) with a bias between 2% (NIR) to 5% (green), which is acceptable given the cumulated limitation in cross-calibration, atmospheric correction and BRDF correction. The second part is devoted to the simulation of the merged Landsat and Sentinel-2 mission by using Landsat-7, LDCM (early) and SPOT-4 Take 5 dataset. SPOT-4 Take 5 dataset is a collection of 42 sites distributed globally and systematically acquired by SPOT-4 HRV every 5 days during the decommissioning phase of the SPOT4 mission (February-May 2013). Finally, the benefits of such a merged surface reflectance at high spatial and temporal resolution are discussed within the context of the agricultural monitoring, in particular in the perspective of the GEOGLAM (Global Earth Observation for Global Land Agriculture Monitoring) project.
Atmospheric correction of AVIRIS data in ocean waters
NASA Technical Reports Server (NTRS)
Terrie, Gregory; Arnone, Robert
1992-01-01
Hyperspectral data offers unique capabilities for characterizing the ocean environment. The spectral characterization of the composition of ocean waters can be organized into biological and terrigenous components. Biological photosynthetic pigments in ocean waters have unique spectral ocean color signatures which can be associated with different biological species. Additionally, suspended sediment has different scattering coefficients which result in ocean color signatures. Measuring the spatial distributions of these components in the maritime environments provides important tools for understanding and monitoring the ocean environment. These tools have significant applications in pollution, carbon cycle, current and water mass detection, location of fronts and eddies, sewage discharge and fate etc. Ocean color was used from satellite for describing the spatial variability of chlorophyll, water clarity (K(sub 490)), suspended sediment concentration, currents etc. Additionally, with improved atmospheric correction methods, ocean color results produced global products of spectral water leaving radiance (L(sub W)). Ocean color results clearly indicated strong applications for characterizing the spatial and temporal variability of bio-optical oceanography. These studies were largely the results of advanced atmospheric correction techniques applied to multispectral imagery. The atmosphere contributes approximately 80 percent - 90 percent of the satellite received radiance in the blue-green portion of the spectrum. In deep ocean waters, maximum transmission of visible radiance is achieved at 490nm. Conversely, nearly all of the light is absorbed by the water at wavelengths greater than about 650nm and thus appears black. These spectral ocean properties are exploited by algorithms developed for the atmospheric correction used in satellite ocean color processing. The objective was to apply atmospheric correction techniques that were used for procesing satellite Coastal Zone Color Scanner (CZCS) data to AVIRIS data. Quantitative measures of L(sub W) from AVIRIS are compared with ship ground truth data and input into bio-optical models.
Nonparametric Bayesian models for a spatial covariance.
Reich, Brian J; Fuentes, Montserrat
2012-01-01
A crucial step in the analysis of spatial data is to estimate the spatial correlation function that determines the relationship between a spatial process at two locations. The standard approach to selecting the appropriate correlation function is to use prior knowledge or exploratory analysis, such as a variogram analysis, to select the correct parametric correlation function. Rather that selecting a particular parametric correlation function, we treat the covariance function as an unknown function to be estimated from the data. We propose a flexible prior for the correlation function to provide robustness to the choice of correlation function. We specify the prior for the correlation function using spectral methods and the Dirichlet process prior, which is a common prior for an unknown distribution function. Our model does not require Gaussian data or spatial locations on a regular grid. The approach is demonstrated using a simulation study as well as an analysis of California air pollution data.
Detection and correction of patient movement in prostate brachytherapy seed reconstruction
NASA Astrophysics Data System (ADS)
Lam, Steve T.; Cho, Paul S.; Marks, Robert J., II; Narayanan, Sreeram
2005-05-01
Intraoperative dosimetry of prostate brachytherapy can help optimize the dose distribution and potentially improve clinical outcome. Evaluation of dose distribution during the seed implant procedure requires the knowledge of 3D seed coordinates. Fluoroscopy-based seed localization is a viable option. From three x-ray projections obtained at different gantry angles, 3D seed positions can be determined. However, when local anaesthesia is used for prostate brachytherapy, the patient movement during fluoroscopy image capture becomes a practical problem. If uncorrected, the errors introduced by patient motion between image captures would cause seed mismatches. Subsequently, the seed reconstruction algorithm would either fail to reconstruct or yield erroneous results. We have developed an algorithm that permits detection and correction of patient movement that may occur between fluoroscopy image captures. The patient movement is decomposed into translational shifts along the tabletop and rotation about an axis perpendicular to the tabletop. The property of spatial invariance of the co-planar imaging geometry is used for lateral movement correction. Cranio-caudal movement is corrected by analysing the perspective invariance along the x-ray axis. Rotation is estimated by an iterative method. The method can detect and correct for the range of patient movement commonly seen in the clinical environment. The algorithm has been implemented for routine clinical use as the preprocessing step for seed reconstruction.
NASA Astrophysics Data System (ADS)
Hartmann, Andreas; Gleeson, Tom; Wada, Yoshihide; Wagener, Thorsten
2016-04-01
Karst develops through the dissolution of carbonate rock. Karst groundwater in Europe is a major source of fresh water contributing up to half of the total drinking water supply in some countries. Climate model projections suggest that in the next 100 years, karst regions will experience a strong increase in temperature and a serious decrease of precipitation - especially in the Mediterranean region. Previous work showed that the karstic preferential recharge processes result in enhanced recharge rates and future climate sensitivity. But as there is fast water flow form the surface to the aquifer, there is also an enhanced risk of groundwater contamination. In this study we will assess the contamination risk of karst aquifers over Europe and the Mediterranean using simulated transit time distributions. Using a new type of semi-distributed model that considers the spatial heterogeneity of the karst system by distribution functions we simulated a range of spatially variable pathways of karstic groundwater recharge. The model is driven by the bias-corrected 5 GCMs of the ISI-MIP project (RCP8.5). Transit time distributions are calculated by virtual tracer experiments. These are repeated several times in the present (1991-2010) and the future (2080-2099). We can show that regions with larger fractions of preferential recharge show higher risks of contamination and that spatial patterns of contamination risk change towards the future.
DOE Office of Scientific and Technical Information (OSTI.GOV)
West, Bradley M.; Stuckelberger, Michael; Jeffries, April
The study of a multilayered and multicomponent system by spatially resolved X-ray fluorescence microscopy poses unique challenges in achieving accurate quantification of elemental distributions. This is particularly true for the quantification of materials with high X-ray attenuation coefficients, depth-dependent composition variations and thickness variations. A widely applicable procedure for use after spectrum fitting and quantification is described. This procedure corrects the elemental distribution from the measured fluorescence signal, taking into account attenuation of the incident beam and generated fluorescence from multiple layers, and accounts for sample thickness variations. Deriving from Beer–Lambert's law, formulae are presented in a general integral formmore » and numerically applicable framework. Here, the procedure is applied using experimental data from a solar cell with a Cu(In,Ga)Se 2 absorber layer, measured at two separate synchrotron beamlines with varied measurement geometries. This example shows the importance of these corrections in real material systems, which can change the interpretation of the measured distributions dramatically.« less
West, Bradley M.; Stuckelberger, Michael; Jeffries, April; ...
2017-01-01
The study of a multilayered and multicomponent system by spatially resolved X-ray fluorescence microscopy poses unique challenges in achieving accurate quantification of elemental distributions. This is particularly true for the quantification of materials with high X-ray attenuation coefficients, depth-dependent composition variations and thickness variations. A widely applicable procedure for use after spectrum fitting and quantification is described. This procedure corrects the elemental distribution from the measured fluorescence signal, taking into account attenuation of the incident beam and generated fluorescence from multiple layers, and accounts for sample thickness variations. Deriving from Beer–Lambert's law, formulae are presented in a general integral formmore » and numerically applicable framework. Here, the procedure is applied using experimental data from a solar cell with a Cu(In,Ga)Se 2 absorber layer, measured at two separate synchrotron beamlines with varied measurement geometries. This example shows the importance of these corrections in real material systems, which can change the interpretation of the measured distributions dramatically.« less
Prediction of Spatiotemporal Patterns of Neural Activity from Pairwise Correlations
DOE Office of Scientific and Technical Information (OSTI.GOV)
Marre, O.; El Boustani, S.; Fregnac, Y.
We designed a model-based analysis to predict the occurrence of population patterns in distributed spiking activity. Using a maximum entropy principle with a Markovian assumption, we obtain a model that accounts for both spatial and temporal pairwise correlations among neurons. This model is tested on data generated with a Glauber spin-glass system and is shown to correctly predict the occurrence probabilities of spatiotemporal patterns significantly better than Ising models only based on spatial correlations. This increase of predictability was also observed on experimental data recorded in parietal cortex during slow-wave sleep. This approach can also be used to generate surrogatesmore » that reproduce the spatial and temporal correlations of a given data set.« less
NASA Technical Reports Server (NTRS)
Brunet, Y.; Vauclin, M.
1985-01-01
The correct interpretation of thermal and hydraulic soil parameters infrared from remotely sensed data (thermal infrared, microwaves) implies a good understanding of the causes of their temporal and spatial variability. Given this necessity, the sensitivity of the surface variables (temperature, moisture) to the spatial variability of hydraulic soil properties is tested with a numerical model of heat and mass transfer between bare soil and atmosphere. The spatial variability of hydraulic soil properties is taken into account in terms of the scaling factor. For a given soil, the knowledge of its frequency distribution allows a stochastic use of the model. The results are treated statistically, and the part of the variability of soil surface parameters due to that of soil hydraulic properties is evaluated quantitatively.
de Lasarte, Marta; Pujol, Jaume; Arjona, Montserrat; Vilaseca, Meritxell
2007-01-10
We present an optimized linear algorithm for the spatial nonuniformity correction of a CCD color camera's imaging system and the experimental methodology developed for its implementation. We assess the influence of the algorithm's variables on the quality of the correction, that is, the dark image, the base correction image, and the reference level, and the range of application of the correction using a uniform radiance field provided by an integrator cube. The best spatial nonuniformity correction is achieved by having a nonzero dark image, by using an image with a mean digital level placed in the linear response range of the camera as the base correction image and taking the mean digital level of the image as the reference digital level. The response of the CCD color camera's imaging system to the uniform radiance field shows a high level of spatial uniformity after the optimized algorithm has been applied, which also allows us to achieve a high-quality spatial nonuniformity correction of captured images under different exposure conditions.
NASA Astrophysics Data System (ADS)
Demirel, Mehmet C.; Mai, Juliane; Mendiguren, Gorka; Koch, Julian; Samaniego, Luis; Stisen, Simon
2018-02-01
Satellite-based earth observations offer great opportunities to improve spatial model predictions by means of spatial-pattern-oriented model evaluations. In this study, observed spatial patterns of actual evapotranspiration (AET) are utilised for spatial model calibration tailored to target the pattern performance of the model. The proposed calibration framework combines temporally aggregated observed spatial patterns with a new spatial performance metric and a flexible spatial parameterisation scheme. The mesoscale hydrologic model (mHM) is used to simulate streamflow and AET and has been selected due to its soil parameter distribution approach based on pedo-transfer functions and the build in multi-scale parameter regionalisation. In addition two new spatial parameter distribution options have been incorporated in the model in order to increase the flexibility of root fraction coefficient and potential evapotranspiration correction parameterisations, based on soil type and vegetation density. These parameterisations are utilised as they are most relevant for simulated AET patterns from the hydrologic model. Due to the fundamental challenges encountered when evaluating spatial pattern performance using standard metrics, we developed a simple but highly discriminative spatial metric, i.e. one comprised of three easily interpretable components measuring co-location, variation and distribution of the spatial data. The study shows that with flexible spatial model parameterisation used in combination with the appropriate objective functions, the simulated spatial patterns of actual evapotranspiration become substantially more similar to the satellite-based estimates. Overall 26 parameters are identified for calibration through a sequential screening approach based on a combination of streamflow and spatial pattern metrics. The robustness of the calibrations is tested using an ensemble of nine calibrations based on different seed numbers using the shuffled complex evolution optimiser. The calibration results reveal a limited trade-off between streamflow dynamics and spatial patterns illustrating the benefit of combining separate observation types and objective functions. At the same time, the simulated spatial patterns of AET significantly improved when an objective function based on observed AET patterns and a novel spatial performance metric compared to traditional streamflow-only calibration were included. Since the overall water balance is usually a crucial goal in hydrologic modelling, spatial-pattern-oriented optimisation should always be accompanied by traditional discharge measurements. In such a multi-objective framework, the current study promotes the use of a novel bias-insensitive spatial pattern metric, which exploits the key information contained in the observed patterns while allowing the water balance to be informed by discharge observations.
Curvature constraints from large scale structure
DOE Office of Scientific and Technical Information (OSTI.GOV)
Dio, Enea Di; Montanari, Francesco; Raccanelli, Alvise
We modified the CLASS code in order to include relativistic galaxy number counts in spatially curved geometries; we present the formalism and study the effect of relativistic corrections on spatial curvature. The new version of the code is now publicly available. Using a Fisher matrix analysis, we investigate how measurements of the spatial curvature parameter Ω {sub K} with future galaxy surveys are affected by relativistic effects, which influence observations of the large scale galaxy distribution. These effects include contributions from cosmic magnification, Doppler terms and terms involving the gravitational potential. As an application, we consider angle and redshift dependentmore » power spectra, which are especially well suited for model independent cosmological constraints. We compute our results for a representative deep, wide and spectroscopic survey, and our results show the impact of relativistic corrections on spatial curvature parameter estimation. We show that constraints on the curvature parameter may be strongly biased if, in particular, cosmic magnification is not included in the analysis. Other relativistic effects turn out to be subdominant in the studied configuration. We analyze how the shift in the estimated best-fit value for the curvature and other cosmological parameters depends on the magnification bias parameter, and find that significant biases are to be expected if this term is not properly considered in the analysis.« less
NASA Astrophysics Data System (ADS)
Vasefi, Fartash; MacKinnon, Nicholas; Saager, Rolf; Kelly, Kristen M.; Maly, Tyler; Booth, Nicholas; Durkin, Anthony J.; Farkas, Daniel L.
2016-11-01
Changes in the pattern and distribution of both melanocytes (pigment producing) and vasculature (hemoglobin containing) are important in distinguishing melanocytic proliferations. The ability to accurately measure melanin distribution at different depths and to distinguish it from hemoglobin is clearly important when assessing pigmented lesions (benign versus malignant). We have developed a multimode hyperspectral dermoscope (SkinSpect™) able to more accurately image both melanin and hemoglobin distribution in skin. SkinSpect uses both hyperspectral and polarization-sensitive measurements. SkinSpect's higher accuracy has been obtained by correcting for the effect of melanin absorption on hemoglobin absorption in measurements of melanocytic nevi. In vivo human skin pigmented nevi (N=20) were evaluated with the SkinSpect, and measured melanin and hemoglobin concentrations were compared with spatial frequency domain spectroscopy (SFDS) measurements. We confirm that both systems show low correlation of hemoglobin concentrations with regions containing different melanin concentrations (R=0.13 for SFDS, R=0.07 for SkinSpect).
Vasefi, Fartash; MacKinnon, Nicholas; Saager, Rolf; Kelly, Kristen M.; Maly, Tyler; Booth, Nicholas; Durkin, Anthony J.; Farkas, Daniel L.
2016-01-01
Abstract. Changes in the pattern and distribution of both melanocytes (pigment producing) and vasculature (hemoglobin containing) are important in distinguishing melanocytic proliferations. The ability to accurately measure melanin distribution at different depths and to distinguish it from hemoglobin is clearly important when assessing pigmented lesions (benign versus malignant). We have developed a multimode hyperspectral dermoscope (SkinSpect™) able to more accurately image both melanin and hemoglobin distribution in skin. SkinSpect uses both hyperspectral and polarization-sensitive measurements. SkinSpect’s higher accuracy has been obtained by correcting for the effect of melanin absorption on hemoglobin absorption in measurements of melanocytic nevi. In vivo human skin pigmented nevi (N=20) were evaluated with the SkinSpect, and measured melanin and hemoglobin concentrations were compared with spatial frequency domain spectroscopy (SFDS) measurements. We confirm that both systems show low correlation of hemoglobin concentrations with regions containing different melanin concentrations (R=0.13 for SFDS, R=0.07 for SkinSpect). PMID:27830262
Vasefi, Fartash; MacKinnon, Nicholas; Saager, Rolf; Kelly, Kristen M; Maly, Tyler; Booth, Nicholas; Durkin, Anthony J; Farkas, Daniel L
2016-11-01
Changes in the pattern and distribution of both melanocytes (pigment producing) and vasculature (hemoglobin containing) are important in distinguishing melanocytic proliferations. The ability to accurately measure melanin distribution at different depths and to distinguish it from hemoglobin is clearly important when assessing pigmented lesions (benign versus malignant). We have developed a multimode hyperspectral dermoscope (SkinSpect™) able to more accurately image both melanin and hemoglobin distribution in skin. SkinSpect uses both hyperspectral and polarization-sensitive measurements. SkinSpect’s higher accuracy has been obtained by correcting for the effect of melanin absorption on hemoglobin absorption in measurements of melanocytic nevi. In vivo human skin pigmented nevi (N=20) were evaluated with the SkinSpect, and measured melanin and hemoglobin concentrations were compared with spatial frequency domain spectroscopy (SFDS) measurements. We confirm that both systems show low correlation of hemoglobin concentrations with regions containing different melanin concentrations (R=0.13 for SFDS, R=0.07 for SkinSpect).
Uncertainty Analysis of Downscaled CMIP5 Precipitation Data for Louisiana, USA
NASA Astrophysics Data System (ADS)
Sumi, S. J.; Tamanna, M.; Chivoiu, B.; Habib, E. H.
2014-12-01
The downscaled CMIP3 and CMIP5 Climate and Hydrology Projections dataset contains fine spatial resolution translations of climate projections over the contiguous United States developed using two downscaling techniques (monthly Bias Correction Spatial Disaggregation (BCSD) and daily Bias Correction Constructed Analogs (BCCA)). The objective of this study is to assess the uncertainty of the CMIP5 downscaled general circulation models (GCM). We performed an analysis of the daily, monthly, seasonal and annual variability of precipitation downloaded from the Downscaled CMIP3 and CMIP5 Climate and Hydrology Projections website for the state of Louisiana, USA at 0.125° x 0.125° resolution. A data set of daily gridded observations of precipitation of a rectangular boundary covering Louisiana is used to assess the validity of 21 downscaled GCMs for the 1950-1999 period. The following statistics are computed using the CMIP5 observed dataset with respect to the 21 models: the correlation coefficient, the bias, the normalized bias, the mean absolute error (MAE), the mean absolute percentage error (MAPE), and the root mean square error (RMSE). A measure of variability simulated by each model is computed as the ratio of its standard deviation, in both space and time, to the corresponding standard deviation of the observation. The correlation and MAPE statistics are also computed for each of the nine climate divisions of Louisiana. Some of the patterns that we observed are: 1) Average annual precipitation rate shows similar spatial distribution for all the models within a range of 3.27 to 4.75 mm/day from Northwest to Southeast. 2) Standard deviation of summer (JJA) precipitation (mm/day) for the models maintains lower value than the observation whereas they have similar spatial patterns and range of values in winter (NDJ). 3) Correlation coefficients of annual precipitation of models against observation have a range of -0.48 to 0.36 with variable spatial distribution by model. 4) Most of the models show negative correlation coefficients in summer and positive in winter. 5) MAE shows similar spatial distribution for all the models within a range of 5.20 to 7.43 mm/day from Northwest to Southeast of Louisiana. 6) Highest values of correlation coefficients are found at seasonal scale within a range of 0.36 to 0.46.
NASA Astrophysics Data System (ADS)
Cannon, Alex J.
2018-01-01
Most bias correction algorithms used in climatology, for example quantile mapping, are applied to univariate time series. They neglect the dependence between different variables. Those that are multivariate often correct only limited measures of joint dependence, such as Pearson or Spearman rank correlation. Here, an image processing technique designed to transfer colour information from one image to another—the N-dimensional probability density function transform—is adapted for use as a multivariate bias correction algorithm (MBCn) for climate model projections/predictions of multiple climate variables. MBCn is a multivariate generalization of quantile mapping that transfers all aspects of an observed continuous multivariate distribution to the corresponding multivariate distribution of variables from a climate model. When applied to climate model projections, changes in quantiles of each variable between the historical and projection period are also preserved. The MBCn algorithm is demonstrated on three case studies. First, the method is applied to an image processing example with characteristics that mimic a climate projection problem. Second, MBCn is used to correct a suite of 3-hourly surface meteorological variables from the Canadian Centre for Climate Modelling and Analysis Regional Climate Model (CanRCM4) across a North American domain. Components of the Canadian Forest Fire Weather Index (FWI) System, a complicated set of multivariate indices that characterizes the risk of wildfire, are then calculated and verified against observed values. Third, MBCn is used to correct biases in the spatial dependence structure of CanRCM4 precipitation fields. Results are compared against a univariate quantile mapping algorithm, which neglects the dependence between variables, and two multivariate bias correction algorithms, each of which corrects a different form of inter-variable correlation structure. MBCn outperforms these alternatives, often by a large margin, particularly for annual maxima of the FWI distribution and spatiotemporal autocorrelation of precipitation fields.
Correction for spatial averaging in laser speckle contrast analysis
Thompson, Oliver; Andrews, Michael; Hirst, Evan
2011-01-01
Practical laser speckle contrast analysis systems face a problem of spatial averaging of speckles, due to the pixel size in the cameras used. Existing practice is to use a system factor in speckle contrast analysis to account for spatial averaging. The linearity of the system factor correction has not previously been confirmed. The problem of spatial averaging is illustrated using computer simulation of time-integrated dynamic speckle, and the linearity of the correction confirmed using both computer simulation and experimental results. The valid linear correction allows various useful compromises in the system design. PMID:21483623
Williams, M.A.; Vondracek, B.
2010-01-01
Karst aquifers are important groundwater resources, but are vulnerable to contamination due to relatively rapid subsurface transport. Springs, points where the landscape and water table intersect and cold groundwater discharges, link aquifer systems with land surfaces and water bodies. As such, in many regions, they are critical to the viability of lakes, streams and cold-water fish communities. An understanding of where springs are located is important to watershed, fishery and environmental management efforts in karst regions. To better understand spatial distribution of springs and as a potential method for identifying variables that characterize locations of springs for improved land and watershed management, a nearest-neighbor analysis and a discriminant function analysis (DFA) of springs were conducted in Winona County, Minnesota USA, a karst landscape. Nearestneighbor analysis examined the spatial spring distribution. Twenty-two variables describing the locations of springs were analyzed to ascertain their ability to discriminate correct aquifer unit or bedrock unit classification for each spring. Springs were clumped with the highest densities in the lowest elevations. Springs were correctly assigned to aquifer units and bedrock units with eight and 11 landscape variables, respectively. Forest land cover was the only land cover type contributing to spring discrimination. Consideration of upland human activities, particularly in forested areas, on spring discharge along with a better understanding of characteristics describing spring locations could lead to better management activities that locate and protect springs and their important contributions to regional ecohydrology. ?? 2010 Springer-Verlag.
Vondracek, Bruce C.; Williams, Mary A.
2010-01-01
Karst aquifers are important groundwater resources, but are vulnerable to contamination due to relatively rapid subsurface transport. Springs, points where the landscape and water table intersect and cold groundwater discharges, link aquifer systems with land surfaces and water bodies. As such, in many regions, they are critical to the viability of lakes, streams and cold-water fish communities. An understanding of where springs are located is important to watershed, fishery and environmental management efforts in karst regions. To better understand spatial distribution of springs and as a potential method for identifying variables that characterize locations of springs for improved land and watershed management, a nearest-neighbor analysis and a discriminant function analysis (DFA) of springs were conducted in Winona County, Minnesota, USA, a karst landscape. Nearest-neighbor analysis examined the spatial spring distribution. Twenty-two variables describing the locations of springs were analyzed to ascertain their ability to discriminate correct aquifer unit or bedrock unit classification for each spring. Springs were clumped with the highest densities in the lowest elevations. Springs were correctly assigned to aquifer units and bedrock units with eight and 11 landscape variables, respectively. Forest land cover was the only land cover type contributing to spring discrimination. Consideration of upland human activities, particularly in forested areas, on spring discharge along with a better understanding of characteristics describing spring locations could lead to better management activities that locate and protect springs and their important contributions to regional ecohydrology.
Cassata, W. S.; Borg, L. E.
2016-05-04
Anomalously old 40Ar/ 39Ar ages are commonly obtained from Shergottites and are generally attributed to uncertainties regarding the isotopic composition of the trapped component and/or the presence of excess 40Ar. Old ages can also be obtained if inaccurate corrections for cosmogenic 36Ar are applied. Current methods for making the cosmogenic correction require simplifying assumptions regarding the spatial homogeneity of target elements for cosmogenic production and the distribution of cosmogenic nuclides relative to trapped and reactor-derived Ar isotopes. To mitigate uncertainties arising from these assumptions, a new cosmogenic correction approach utilizing the exposure age determined on an un-irradiated aliquot and step-wisemore » production rate estimates that account for spatial variations in Ca and K is described. Data obtained from NWA 4468 and an unofficial pairing of NWA 2975, which yield anomalously old ages when corrected for cosmogenic 36Ar using conventional techniques, are used to illustrate the efficacy of this new approach. For these samples, anomalous age determinations are rectified solely by the improved cosmogenic correction technique described herein. Ages of 188 ± 17 and 184 ± 17 Ma are obtained for NWA 4468 and NWA 2975, respectively, both of which are indistinguishable from ages obtained by other radioisotopic systems. For other Shergottites that have multiple trapped components, have experienced diffusive loss of Ar, or contain excess Ar, more accurate cosmogenic corrections may aid in the interpretation of anomalous ages. In conclusion, the trapped 40Ar/ 36Ar ratios inferred from inverse isochron diagrams obtained from NWA 4468 and NWA 2975 are significantly lower than the Martian atmospheric value, and may represent upper mantle or crustal components.« less
Spatial Point Pattern Analysis of Neurons Using Ripley's K-Function in 3D
Jafari-Mamaghani, Mehrdad; Andersson, Mikael; Krieger, Patrik
2010-01-01
The aim of this paper is to apply a non-parametric statistical tool, Ripley's K-function, to analyze the 3-dimensional distribution of pyramidal neurons. Ripley's K-function is a widely used tool in spatial point pattern analysis. There are several approaches in 2D domains in which this function is executed and analyzed. Drawing consistent inferences on the underlying 3D point pattern distributions in various applications is of great importance as the acquisition of 3D biological data now poses lesser of a challenge due to technological progress. As of now, most of the applications of Ripley's K-function in 3D domains do not focus on the phenomenon of edge correction, which is discussed thoroughly in this paper. The main goal is to extend the theoretical and practical utilization of Ripley's K-function and corresponding tests based on bootstrap resampling from 2D to 3D domains. PMID:20577588
NASA Astrophysics Data System (ADS)
Russell, Matthew J.; Jensen, Oliver E.; Galla, Tobias
2016-10-01
Motivated by uncertainty quantification in natural transport systems, we investigate an individual-based transport process involving particles undergoing a random walk along a line of point sinks whose strengths are themselves independent random variables. We assume particles are removed from the system via first-order kinetics. We analyze the system using a hierarchy of approaches when the sinks are sparsely distributed, including a stochastic homogenization approximation that yields explicit predictions for the extrinsic disorder in the stationary state due to sink strength fluctuations. The extrinsic noise induces long-range spatial correlations in the particle concentration, unlike fluctuations due to the intrinsic noise alone. Additionally, the mean concentration profile, averaged over both intrinsic and extrinsic noise, is elevated compared with the corresponding profile from a uniform sink distribution, showing that the classical homogenization approximation can be a biased estimator of the true mean.
The assessment of spatial distribution of soil salinity risk using neural network.
Akramkhanov, Akmal; Vlek, Paul L G
2012-04-01
Soil salinity in the Aral Sea Basin is one of the major limiting factors of sustainable crop production. Leaching of the salts before planting season is usually a prerequisite for crop establishment and predetermined water amounts are applied uniformly to fields often without discerning salinity levels. The use of predetermined water amounts for leaching perhaps partly emanate from the inability of conventional soil salinity surveys (based on collection of soil samples, laboratory analyses) to generate timely and high-resolution salinity maps. This paper has an objective to estimate the spatial distribution of soil salinity based on readily or cheaply obtainable environmental parameters (terrain indices, remote sensing data, distance to drains, and long-term groundwater observation data) using a neural network model. The farm-scale (∼15 km(2)) results were used to upscale soil salinity to a district area (∼300 km(2)). The use of environmental attributes and soil salinity relationships to upscale the spatial distribution of soil salinity from farm to district scale resulted in the estimation of essentially similar average soil salinity values (estimated 0.94 vs. 1.04 dS m(-1)). Visual comparison of the maps suggests that the estimated map had soil salinity that was uniform in distribution. The upscaling proved to be satisfactory; depending on critical salinity threshold values, around 70-90% of locations were correctly estimated.
The Use of a Predictive Habitat Model and a Fuzzy Logic Approach for Marine Management and Planning
Hattab, Tarek; Ben Rais Lasram, Frida; Albouy, Camille; Sammari, Chérif; Romdhane, Mohamed Salah; Cury, Philippe; Leprieur, Fabien; Le Loc’h, François
2013-01-01
Bottom trawl survey data are commonly used as a sampling technique to assess the spatial distribution of commercial species. However, this sampling technique does not always correctly detect a species even when it is present, and this can create significant limitations when fitting species distribution models. In this study, we aim to test the relevance of a mixed methodological approach that combines presence-only and presence-absence distribution models. We illustrate this approach using bottom trawl survey data to model the spatial distributions of 27 commercially targeted marine species. We use an environmentally- and geographically-weighted method to simulate pseudo-absence data. The species distributions are modelled using regression kriging, a technique that explicitly incorporates spatial dependence into predictions. Model outputs are then used to identify areas that met the conservation targets for the deployment of artificial anti-trawling reefs. To achieve this, we propose the use of a fuzzy logic framework that accounts for the uncertainty associated with different model predictions. For each species, the predictive accuracy of the model is classified as ‘high’. A better result is observed when a large number of occurrences are used to develop the model. The map resulting from the fuzzy overlay shows that three main areas have a high level of agreement with the conservation criteria. These results align with expert opinion, confirming the relevance of the proposed methodology in this study. PMID:24146867
Multicenter reliability of semiautomatic retinal layer segmentation using OCT
Oberwahrenbrock, Timm; Traber, Ghislaine L.; Lukas, Sebastian; Gabilondo, Iñigo; Nolan, Rachel; Songster, Christopher; Balk, Lisanne; Petzold, Axel; Paul, Friedemann; Villoslada, Pablo; Brandt, Alexander U.; Green, Ari J.
2018-01-01
Objective To evaluate the inter-rater reliability of semiautomated segmentation of spectral domain optical coherence tomography (OCT) macular volume scans. Methods Macular OCT volume scans of left eyes from 17 subjects (8 patients with MS and 9 healthy controls) were automatically segmented by Heidelberg Eye Explorer (v1.9.3.0) beta-software (Spectralis Viewing Module v6.0.0.7), followed by manual correction by 5 experienced operators from 5 different academic centers. The mean thicknesses within a 6-mm area around the fovea were computed for the retinal nerve fiber layer, ganglion cell layer (GCL), inner plexiform layer (IPL), inner nuclear layer, outer plexiform layer (OPL), and outer nuclear layer (ONL). Intraclass correlation coefficients (ICCs) were calculated for mean layer thickness values. Spatial distribution of ICC values for the segmented volume scans was investigated using heat maps. Results Agreement between raters was good (ICC > 0.84) for all retinal layers, particularly inner retinal layers showed excellent agreement across raters (ICC > 0.96). Spatial distribution of ICC showed highest values in the perimacular area, whereas the ICCs were poorer for the foveola and the more peripheral macular area. The automated segmentation of the OPL and ONL required the most correction and showed the least agreement, whereas differences were less prominent for the remaining layers. Conclusions Automated segmentation with manual correction of macular OCT scans is highly reliable when performed by experienced raters and can thus be applied in multicenter settings. Reliability can be improved by restricting analysis to the perimacular area and compound segmentation of GCL and IPL. PMID:29552598
Grech, Alana; Sheppard, James; Marsh, Helene
2011-01-01
Background Conservation planning and the design of marine protected areas (MPAs) requires spatially explicit information on the distribution of ecological features. Most species of marine mammals range over large areas and across multiple planning regions. The spatial distributions of marine mammals are difficult to predict using habitat modelling at ecological scales because of insufficient understanding of their habitat needs, however, relevant information may be available from surveys conducted to inform mandatory stock assessments. Methodology and Results We use a 20-year time series of systematic aerial surveys of dugong (Dugong dugong) abundance to create spatially-explicit models of dugong distribution and relative density at the scale of the coastal waters of northeast Australia (∼136,000 km2). We interpolated the corrected data at the scale of 2 km * 2 km planning units using geostatistics. Planning units were classified as low, medium, high and very high dugong density on the basis of the relative density of dugongs estimated from the models and a frequency analysis. Torres Strait was identified as the most significant dugong habitat in northeast Australia and the most globally significant habitat known for any member of the Order Sirenia. The models are used by local, State and Federal agencies to inform management decisions related to the Indigenous harvest of dugongs, gill-net fisheries and Australia's National Representative System of Marine Protected Areas. Conclusion/Significance In this paper we demonstrate that spatially-explicit population models add value to data collected for stock assessments, provide a robust alternative to predictive habitat distribution models, and inform species conservation at multiple scales. PMID:21464933
NASA Astrophysics Data System (ADS)
Fu, Z.; Qin, Q.; Wu, C.; Chang, Y.; Luo, B.
2017-09-01
Due to the differences of imaging principles, image matching between visible and thermal infrared images still exist new challenges and difficulties. Inspired by the complementary spatial and frequency information of geometric structural features, a robust descriptor is proposed for visible and thermal infrared images matching. We first divide two different spatial regions to the region around point of interest, using the histogram of oriented magnitudes, which corresponds to the 2-D structural shape information to describe the larger region and the edge oriented histogram to describe the spatial distribution for the smaller region. Then the two vectors are normalized and combined to a higher feature vector. Finally, our proposed descriptor is obtained by applying principal component analysis (PCA) to reduce the dimension of the combined high feature vector to make our descriptor more robust. Experimental results showed that our proposed method was provided with significant improvements in correct matching numbers and obvious advantages by complementing information within spatial and frequency structural information.
Topographic correction realization based on the CBERS-02B image
NASA Astrophysics Data System (ADS)
Qin, Hui-ping; Yi, Wei-ning; Fang, Yong-hua
2011-08-01
The special topography of mountain terrain will induce the retrieval distortion in same species and surface spectral lines. In order to improve the research accuracy of topographic surface characteristic, many researchers have focused on topographic correction. Topographic correction methods can be statistical-empirical model or physical model, in which the methods based on the digital elevation model data are most popular. Restricted by spatial resolution, previous model mostly corrected topographic effect based on Landsat TM image, whose spatial resolution is 30 meter that can be easily achieved from internet or calculated from digital map. Some researchers have also done topographic correction based on high spatial resolution images, such as Quickbird and Ikonos, but there is little correlative research on the topographic correction of CBERS-02B image. In this study, liao-ning mountain terrain was taken as the objective. The digital elevation model data was interpolated to 2.36 meter by 15 meter original digital elevation model one meter by one meter. The C correction, SCS+C correction, Minnaert correction and Ekstrand-r were executed to correct the topographic effect. Then the corrected results were achieved and compared. The images corrected with C correction, SCS+C correction, Minnaert correction and Ekstrand-r were compared, and the scatter diagrams between image digital number and cosine of solar incidence angel with respect to surface normal were shown. The mean value, standard variance, slope of scatter diagram, and separation factor were statistically calculated. The analysed result shows that the shadow is weakened in corrected images than the original images, and the three-dimensional affect is removed. The absolute slope of fitting lines in scatter diagram is minished. Minnaert correction method has the most effective result. These demonstrate that the former correction methods can be successfully adapted to CBERS-02B images. The DEM data can be interpolated step by step to get the corresponding spatial resolution approximately for the condition that high spatial resolution elevation data is hard to get.
Remote sensing of chlorophyll concentrations in the northern Gulf of Mexico
NASA Technical Reports Server (NTRS)
Trees, Charles C.; El-Sayed, Sayed Z.
1986-01-01
During a 17 month period (November 1978 - March 1980), phytoplankton pigment concentrations were remotely sensed in the northern Gulf of Mexico using the Coastal Zone Color Scanner (CZCS). A total of 29 CZCS orbits were processed into pigment (chlorophyll a + phaeopigments) images and then geometrically warped to a Mercator projection. A correction factor of 1.67 was applied to the pigment concentrations to correct for the tendency of the standard fluorometric method to underestimate chlorophyll a concentrations. The spatial and temporal distributions of pigment fronts were quite variable during this time series. Constant features observed throughout the pigment imagery were the entrainment of coastal waters offshore. The most extensive entrainments occurred during intrusions of the Loop Current. For the 17 month survey, the mean HPLC-corrected pigment concentration was 3.30 + or - 1.45 mg/cu m.
Perceived image quality with simulated segmented bifocal corrections
Dorronsoro, Carlos; Radhakrishnan, Aiswaryah; de Gracia, Pablo; Sawides, Lucie; Marcos, Susana
2016-01-01
Bifocal contact or intraocular lenses use the principle of simultaneous vision to correct for presbyopia. A modified two-channel simultaneous vision simulator provided with an amplitude transmission spatial light modulator was used to optically simulate 14 segmented bifocal patterns (+ 3 diopters addition) with different far/near pupillary distributions of equal energy. Five subjects with paralyzed accommodation evaluated image quality and subjective preference through the segmented bifocal corrections. There are strong and systematic perceptual differences across the patterns, subjects and observation distances: 48% of the conditions evaluated were significantly preferred or rejected. Optical simulations (in terms of through-focus Strehl ratio from Hartmann-Shack aberrometry) accurately predicted the pattern producing the highest perceived quality in 4 out of 5 patients, both for far and near vision. These perceptual differences found arise primarily from optical grounds, but have an important neural component. PMID:27895981
NASA Astrophysics Data System (ADS)
Frances, F.; Orozco, I.
2010-12-01
This work presents the assessment of the TETIS distributed hydrological model in mountain basins of the American and Carson rivers in Sierra Nevada (USA) at hourly time discretization, as part of the DMIP2 Project. In TETIS each cell of the spatial grid conceptualizes the water cycle using six tanks connected among them. The relationship between tanks depends on the case, although at the end in most situations, simple linear reservoirs and flow thresholds schemes are used with exceptional results (Vélez et al., 1999; Francés et al., 2002). In particular, within the snow tank, snow melting is based in this work on the simple degree-day method with spatial constant parameters. The TETIS model includes an automatic calibration module, based on the SCE-UA algorithm (Duan et al., 1992; Duan et al., 1994) and the model effective parameters are organized following a split structure, as presented by Francés and Benito (1995) and Francés et al. (2007). In this way, the calibration involves in TETIS up to 9 correction factors (CFs), which correct globally the different parameter maps instead of each parameter cell value, thus reducing drastically the number of variables to be calibrated. This strategy allows for a fast and agile modification in different hydrological processes preserving the spatial structure of each parameter map. With the snowmelt submodel, automatic model calibration was carried out in three steps, separating the calibration of rainfall-runoff and snowmelt parameters. In the first step, the automatic calibration of the CFs during the period 05/20/1990 to 07/31/1990 in the American River (without snow influence), gave a Nash-Sutcliffe Efficiency (NSE) index of 0.92. The calibration of the three degree-day parameters was done using all the SNOTEL stations in the American and Carson rivers. Finally, using previous calibrations as initial values, the complete calibration done in the Carson River for the period 10/01/1992 to 07/31/1993 gave a NSE index of 0.86. The temporal and spatial validation using five periods must be considered in both rivers excellent for discharges (NSEs higher than 0.76) and good for snow distribution (daily spatial coverage errors ranging from -10 to 27%). In conclusion, this work demonstrates: 1.- The viability of automatic calibration of distributed models, with the corresponding personal time saving and maximum exploitation of the available information. 2.- The good performance of the degree-day snowmelt formulation even at hourly time discretization, in spite of its simplicity.
Direct Reconstruction of CT-Based Attenuation Correction Images for PET With Cluster-Based Penalties
NASA Astrophysics Data System (ADS)
Kim, Soo Mee; Alessio, Adam M.; De Man, Bruno; Kinahan, Paul E.
2017-03-01
Extremely low-dose (LD) CT acquisitions used for PET attenuation correction have high levels of noise and potential bias artifacts due to photon starvation. This paper explores the use of a priori knowledge for iterative image reconstruction of the CT-based attenuation map. We investigate a maximum a posteriori framework with cluster-based multinomial penalty for direct iterative coordinate decent (dICD) reconstruction of the PET attenuation map. The objective function for direct iterative attenuation map reconstruction used a Poisson log-likelihood data fit term and evaluated two image penalty terms of spatial and mixture distributions. The spatial regularization is based on a quadratic penalty. For the mixture penalty, we assumed that the attenuation map may consist of four material clusters: air + background, lung, soft tissue, and bone. Using simulated noisy sinogram data, dICD reconstruction was performed with different strengths of the spatial and mixture penalties. The combined spatial and mixture penalties reduced the root mean squared error (RMSE) by roughly two times compared with a weighted least square and filtered backprojection reconstruction of CT images. The combined spatial and mixture penalties resulted in only slightly lower RMSE compared with a spatial quadratic penalty alone. For direct PET attenuation map reconstruction from ultra-LD CT acquisitions, the combination of spatial and mixture penalties offers regularization of both variance and bias and is a potential method to reconstruct attenuation maps with negligible patient dose. The presented results, using a best-case histogram suggest that the mixture penalty does not offer a substantive benefit over conventional quadratic regularization and diminishes enthusiasm for exploring future application of the mixture penalty.
Mapping Mediterranean seagrasses with Sentinel-2 imagery.
Traganos, Dimosthenis; Reinartz, Peter
2017-07-01
Mediterranean seagrasses have been hailed for their numerous ecosystem services, yet they are undergoing a decline in their coverage. The major complication with resolving this tendency is the sparsity of data on their overall distribution. This study addresses the suitability of the recently launched Sentinel-2 satellite for mapping the distribution of Mediterranean seagrass meadows. A comprehensive methodology is presented which applies atmospheric and analytical water column corrections and compares the performance of three different supervised classifiers. Remote sensing of the Thermaikos Gulf, northwestern Aegean Sea (Greece, eastern Mediterranean Sea) reveals that the utilization of Support Vector Machines on water column corrected reflectances yields best accuracies. Two Mediterranean seagrasses, Posidonia oceanica and Cymodocea nodosa, cover a total submerged area of 1.48km 2 between depths of 1.4-16.5m. With its 10-m spatial resolution and 5-day revisit frequency, Sentinel-2 imagery can mitigate the Mediterranean seagrass distribution data gap and allow better management and conservation in the future in a retrospective, time- and cost-effective fashion. Copyright © 2017 Elsevier Ltd. All rights reserved.
NASA Astrophysics Data System (ADS)
Khan, S.; Salas, F.; Sampson, K. M.; Read, L. K.; Cosgrove, B.; Li, Z.; Gochis, D. J.
2017-12-01
The representation of inland surface water bodies in distributed hydrologic models at the continental scale is a challenge. The National Water Model (NWM) utilizes the National Hydrography Dataset Plus Version 2 (NHDPlusV2) "waterbody" dataset to represent lakes and reservoirs. The "waterbody" layer is a comprehensive dataset that represents surface water bodies using common features like lakes, ponds, reservoirs, estuaries, playas and swamps/marshes. However, a major issue that remains unresolved even in the latest revision of NHDPlus Version 2 is the inconsistency in waterbody digitization and delineation errors. Manually correcting the water body polygons becomes tedious and quickly impossible for continental-scale hydrologic models such as the NWM. In this study, we improved spatial representation of 6,802 lakes and reservoirs by analyzing 379,110 waterbodies in the contiguous United States (excluding the Laurentian Great Lakes). We performed a step-by- step process that integrates a set of geospatial analyses to identify, track, and correct the extent of lakes and reservoirs features that are larger than 0.75 km2. The following assumptions were applied while developing the new dataset: a) lakes and reservoirs cannot directly feed into each other; b) each waterbody must have one outlet; and c) a single lake or reservoir feature cannot have multiple parts. The majority of the NHDplusV2 waterbody features in the original dataset are delineated correctly. However approximately 3 % of the lake and reservoir polygons were found to be incorrect with topological errors and were corrected accordingly. It is important to fix these digitizing errors because the waterbody features are closely linked to the river topology. This new waterbody dataset will ensure that model-simulated water is directed into and through the lakes and reservoirs in a manner that supports the NWM code base and assumptions. The improved dataset will facilitate more effective integration of lakes and reservoirs with correct spatial features into the updated NWM.
A new method for spatial structure detection of complex inner cavities based on 3D γ-photon imaging
NASA Astrophysics Data System (ADS)
Xiao, Hui; Zhao, Min; Liu, Jiantang; Liu, Jiao; Chen, Hao
2018-05-01
This paper presents a new three-dimensional (3D) imaging method for detecting the spatial structure of a complex inner cavity based on positron annihilation and γ-photon detection. This method first marks carrier solution by a certain radionuclide and injects it into the inner cavity where positrons are generated. Subsequently, γ-photons are released from positron annihilation, and the γ-photon detector ring is used for recording the γ-photons. Finally, the two-dimensional (2D) image slices of the inner cavity are constructed by the ordered-subset expectation maximization scheme and the 2D image slices are merged to the 3D image of the inner cavity. To eliminate the artifact in the reconstructed image due to the scattered γ-photons, a novel angle-traversal model is proposed for γ-photon single-scattering correction, in which the path of the single scattered γ-photon is analyzed from a spatial geometry perspective. Two experiments are conducted to verify the effectiveness of the proposed correction model and the advantage of the proposed testing method in detecting the spatial structure of the inner cavity, including the distribution of gas-liquid multi-phase mixture inside the inner cavity. The above two experiments indicate the potential of the proposed method as a new tool for accurately delineating the inner structures of industrial complex parts.
Photofragment image analysis using the Onion-Peeling Algorithm
NASA Astrophysics Data System (ADS)
Manzhos, Sergei; Loock, Hans-Peter
2003-07-01
With the growing popularity of the velocity map imaging technique, a need for the analysis of photoion and photoelectron images arose. Here, a computer program is presented that allows for the analysis of cylindrically symmetric images. It permits the inversion of the projection of the 3D charged particle distribution using the Onion Peeling Algorithm. Further analysis includes the determination of radial and angular distributions, from which velocity distributions and spatial anisotropy parameters are obtained. Identification and quantification of the different photolysis channels is therefore straightforward. In addition, the program features geometry correction, centering, and multi-Gaussian fitting routines, as well as a user-friendly graphical interface and the possibility of generating synthetic images using either the fitted or user-defined parameters. Program summaryTitle of program: Glass Onion Catalogue identifier: ADRY Program Summary URL:http://cpc.cs.qub.ac.uk/summaries/ADRY Program obtainable from: CPC Program Library, Queen's University of Belfast, N. Ireland Licensing provisions: none Computer: IBM PC Operating system under which the program has been tested: Windows 98, Windows 2000, Windows NT Programming language used: Delphi 4.0 Memory required to execute with typical data: 18 Mwords No. of bits in a word: 32 No. of bytes in distributed program, including test data, etc.: 9 911 434 Distribution format: zip file Keywords: Photofragment image, onion peeling, anisotropy parameters Nature of physical problem: Information about velocity and angular distributions of photofragments is the basis on which the analysis of the photolysis process resides. Reconstructing the three-dimensional distribution from the photofragment image is the first step, further processing involving angular and radial integration of the inverted image to obtain velocity and angular distributions. Provisions have to be made to correct for slight distortions of the image, and to verify the accuracy of the analysis process. Method of solution: The "Onion Peeling" algorithm described by Helm [Rev. Sci. Instrum. 67 (6) (1996)] is used to perform the image reconstruction. Angular integration with a subsequent multi-Gaussian fit supplies information about the velocity distribution of the photofragments, whereas radial integration with subsequent expansion of the angular distributions over Legendre Polynomials gives the spatial anisotropy parameters. Fitting algorithms have been developed to centre the image and to correct for image distortion. Restrictions on the complexity of the problem: The maximum image size (1280×1280) and resolution (16 bit) are restricted by available memory and can be changed in the source code. Initial centre coordinates within 5 pixels may be required for the correction and the centering algorithm to converge. Peaks on the velocity profile separated by less then the peak width may not be deconvolved. In the charged particle image reconstruction, it is assumed that the kinetic energy released in the dissociation process is small compared to the energy acquired in the electric field. For the fitting parameters to be physically meaningful, cylindrical symmetry of the image has to be assumed but the actual inversion algorithm is stable to distortions of such symmetry in experimental images. Typical running time: The analysis procedure can be divided into three parts: inversion, fitting, and geometry correction. The inversion time grows approx. as R3, where R is the radius of the region of interest: for R=200 pixels it is less than a minute, for R=400 pixels less then 6 min on a 400 MHz IBM personal computer. The time for the velocity fitting procedure to converge depends strongly on the number of peaks in the velocity profile and the convergence criterion. It ranges between less then a second for simple curves and a few minutes for profiles with up to twenty peaks. The time taken for the image correction scales as R2 and depends on the curve profile. It is on the order of a few minutes for images with R=500 pixels. Unusual features of the program: Our centering and image correction algorithm is based on Fourier analysis of the radial distribution to insure the sharpest velocity profile and is insensitive to an uneven intensity distribution. There exists an angular averaging option to stabilize the inversion algorithm and not to loose the resolution at the same time.
NASA Astrophysics Data System (ADS)
Dumouchel, Tyler; Thorn, Stephanie; Kordos, Myra; DaSilva, Jean; Beanlands, Rob S. B.; deKemp, Robert A.
2012-07-01
Quantification in cardiac mouse positron emission tomography (PET) imaging is limited by the imaging spatial resolution. Spillover of left ventricle (LV) myocardial activity into adjacent organs results in partial volume (PV) losses leading to underestimation of myocardial activity. A PV correction method was developed to restore accuracy of the activity distribution for FDG mouse imaging. The PV correction model was based on convolving an LV image estimate with a 3D point spread function. The LV model was described regionally by a five-parameter profile including myocardial, background and blood activities which were separated into three compartments by the endocardial radius and myocardium wall thickness. The PV correction was tested with digital simulations and a physical 3D mouse LV phantom. In vivo cardiac FDG mouse PET imaging was also performed. Following imaging, the mice were sacrificed and the tracer biodistribution in the LV and liver tissue was measured using a gamma-counter. The PV correction algorithm improved recovery from 50% to within 5% of the truth for the simulated and measured phantom data and image uniformity by 5-13%. The PV correction algorithm improved the mean myocardial LV recovery from 0.56 (0.54) to 1.13 (1.10) without (with) scatter and attenuation corrections. The mean image uniformity was improved from 26% (26%) to 17% (16%) without (with) scatter and attenuation corrections applied. Scatter and attenuation corrections were not observed to significantly impact PV-corrected myocardial recovery or image uniformity. Image-based PV correction algorithm can increase the accuracy of PET image activity and improve the uniformity of the activity distribution in normal mice. The algorithm may be applied using different tracers, in transgenic models that affect myocardial uptake, or in different species provided there is sufficient image quality and similar contrast between the myocardium and surrounding structures.
NASA Astrophysics Data System (ADS)
Passow, Christian; Donner, Reik
2017-04-01
Quantile mapping (QM) is an established concept that allows to correct systematic biases in multiple quantiles of the distribution of a climatic observable. It shows remarkable results in correcting biases in historical simulations through observational data and outperforms simpler correction methods which relate only to the mean or variance. Since it has been shown that bias correction of future predictions or scenario runs with basic QM can result in misleading trends in the projection, adjusted, trend preserving, versions of QM were introduced in the form of detrended quantile mapping (DQM) and quantile delta mapping (QDM) (Cannon, 2015, 2016). Still, all previous versions and applications of QM based bias correction rely on the assumption of time-independent quantiles over the investigated period, which can be misleading in the context of a changing climate. Here, we propose a novel combination of linear quantile regression (QR) with the classical QM method to introduce a consistent, time-dependent and trend preserving approach of bias correction for historical and future projections. Since QR is a regression method, it is possible to estimate quantiles in the same resolution as the given data and include trends or other dependencies. We demonstrate the performance of the new method of linear regression quantile mapping (RQM) in correcting biases of temperature and precipitation products from historical runs (1959 - 2005) of the COSMO model in climate mode (CCLM) from the Euro-CORDEX ensemble relative to gridded E-OBS data of the same spatial and temporal resolution. A thorough comparison with established bias correction methods highlights the strengths and potential weaknesses of the new RQM approach. References: A.J. Cannon, S.R. Sorbie, T.Q. Murdock: Bias Correction of GCM Precipitation by Quantile Mapping - How Well Do Methods Preserve Changes in Quantiles and Extremes? Journal of Climate, 28, 6038, 2015 A.J. Cannon: Multivariate Bias Correction of Climate Model Outputs - Matching Marginal Distributions and Inter-variable Dependence Structure. Journal of Climate, 29, 7045, 2016
NASA Technical Reports Server (NTRS)
Pagnutti, Mary
2006-01-01
This viewgraph presentation reviews the creation of a prototype algorithm for atmospheric correction using high spatial resolution earth observing imaging systems. The objective of the work was to evaluate accuracy of a prototype algorithm that uses satellite-derived atmospheric products to generate scene reflectance maps for high spatial resolution (HSR) systems. This presentation focused on preliminary results of only the satellite-based atmospheric correction algorithm.
Statistical Maps of Ground Magnetic Disturbance Derived from Global Geospace Models
NASA Astrophysics Data System (ADS)
Rigler, E. J.; Wiltberger, M. J.; Love, J. J.
2017-12-01
Electric currents in space are the principal driver of magnetic variations measured at Earth's surface. These in turn induce geoelectric fields that present a natural hazard for technological systems like high-voltage power distribution networks. Modern global geospace models can reasonably simulate large-scale geomagnetic response to solar wind variations, but they are less successful at deterministic predictions of intense localized geomagnetic activity that most impacts technological systems on the ground. Still, recent studies have shown that these models can accurately reproduce the spatial statistical distributions of geomagnetic activity, suggesting that their physics are largely correct. Since the magnetosphere is a largely externally driven system, most model-measurement discrepancies probably arise from uncertain boundary conditions. So, with realistic distributions of solar wind parameters to establish its boundary conditions, we use the Lyon-Fedder-Mobarry (LFM) geospace model to build a synthetic multivariate statistical model of gridded ground magnetic disturbance. From this, we analyze the spatial modes of geomagnetic response, regress on available measurements to fill in unsampled locations on the grid, and estimate the global probability distribution of extreme magnetic disturbance. The latter offers a prototype geomagnetic "hazard map", similar to those used to characterize better-known geophysical hazards like earthquakes and floods.
NASA Astrophysics Data System (ADS)
Ossés de Eicker, Margarita; Zah, Rainer; Triviño, Rubén; Hurni, Hans
The spatial accuracy of top-down traffic emission inventory maps obtained with a simplified disaggregation method based on street density was assessed in seven mid-sized Chilean cities. Each top-down emission inventory map was compared against a reference, namely a more accurate bottom-up emission inventory map from the same study area. The comparison was carried out using a combination of numerical indicators and visual interpretation. Statistically significant differences were found between the seven cities with regard to the spatial accuracy of their top-down emission inventory maps. In compact cities with a simple street network and a single center, a good accuracy of the spatial distribution of emissions was achieved with correlation values>0.8 with respect to the bottom-up emission inventory of reference. In contrast, the simplified disaggregation method is not suitable for complex cities consisting of interconnected nuclei, resulting in correlation values<0.5. Although top-down disaggregation of traffic emissions generally exhibits low accuracy, the accuracy is significantly higher in compact cities and might be further improved by applying a correction factor for the city center. Therefore, the method can be used by local environmental authorities in cities with limited resources and with little knowledge on the pollution situation to get an overview on the spatial distribution of the emissions generated by traffic activities.
Ponomarev, Artem L; Costes, Sylvain V; Cucinotta, Francis A
2008-11-01
We computed probabilities to have multiple double-strand breaks (DSB), which are produced in DNA on a regional scale, and not in close vicinity, in volumes matching the size of DNA damage foci, of a large chromatin loop, and in the physical volume of DNA containing the HPRT (human hypoxanthine phosphoribosyltransferase) locus. The model is based on a Monte Carlo description of DSB formation by heavy ions in the spatial context of the entire human genome contained within the cell nucleus, as well as at the gene sequence level. We showed that a finite physical volume corresponding to a visible DNA repair focus, believed to be associated with one DSB, can contain multiple DSB due to heavy ion track structure and the DNA supercoiled topography. A corrective distribution was introduced, which was a conditional probability to have excess DSB in a focus volume, given that there was already one present. The corrective distribution was calculated for 19.5 MeV/amu N ions, 3.77 MeV/amu alpha-particles, 1000 MeV/amu Fe ions, and X-rays. The corrected initial DSB yield from the experimental data on DNA repair foci was calculated. The DSB yield based on the corrective function converts the focus yield into the DSB yield, which is comparable with the DSB yield based on the earlier PFGE experiments. The distribution of DSB within the physical limits of the HPRT gene was analyzed by a similar method as well. This corrective procedure shows the applicability of the model and empowers the researcher with a tool to better analyze focus statistics. The model enables researchers to analyze the DSB yield based on focus statistics in real experimental situations that lack one-to-one focus-to-DSB correspondance.
Hydrologic extremes - an intercomparison of multiple gridded statistical downscaling methods
NASA Astrophysics Data System (ADS)
Werner, A. T.; Cannon, A. J.
2015-06-01
Gridded statistical downscaling methods are the main means of preparing climate model data to drive distributed hydrological models. Past work on the validation of climate downscaling methods has focused on temperature and precipitation, with less attention paid to the ultimate outputs from hydrological models. Also, as attention shifts towards projections of extreme events, downscaling comparisons now commonly assess methods in terms of climate extremes, but hydrologic extremes are less well explored. Here, we test the ability of gridded downscaling models to replicate historical properties of climate and hydrologic extremes, as measured in terms of temporal sequencing (i.e., correlation tests) and distributional properties (i.e., tests for equality of probability distributions). Outputs from seven downscaling methods - bias correction constructed analogues (BCCA), double BCCA (DBCCA), BCCA with quantile mapping reordering (BCCAQ), bias correction spatial disaggregation (BCSD), BCSD using minimum/maximum temperature (BCSDX), climate imprint delta method (CI), and bias corrected CI (BCCI) - are used to drive the Variable Infiltration Capacity (VIC) model over the snow-dominated Peace River basin, British Columbia. Outputs are tested using split-sample validation on 26 climate extremes indices (ClimDEX) and two hydrologic extremes indices (3 day peak flow and 7 day peak flow). To characterize observational uncertainty, four atmospheric reanalyses are used as climate model surrogates and two gridded observational datasets are used as downscaling target data. The skill of the downscaling methods generally depended on reanalysis and gridded observational dataset. However, CI failed to reproduce the distribution and BCSD and BCSDX the timing of winter 7 day low flow events, regardless of reanalysis or observational dataset. Overall, DBCCA passed the greatest number of tests for the ClimDEX indices, while BCCAQ, which is designed to more accurately resolve event-scale spatial gradients, passed the greatest number of tests for hydrologic extremes. Non-stationarity in the observational/reanalysis datasets complicated the evaluation of downscaling performance. Comparing temporal homogeneity and trends in climate indices and hydrological model outputs calculated from downscaled reanalyses and gridded observations was useful for diagnosing the reliability of the various historical datasets. We recommend that such analyses be conducted before such data are used to construct future hydro-climatic change scenarios.
Hydrologic extremes - an intercomparison of multiple gridded statistical downscaling methods
NASA Astrophysics Data System (ADS)
Werner, Arelia T.; Cannon, Alex J.
2016-04-01
Gridded statistical downscaling methods are the main means of preparing climate model data to drive distributed hydrological models. Past work on the validation of climate downscaling methods has focused on temperature and precipitation, with less attention paid to the ultimate outputs from hydrological models. Also, as attention shifts towards projections of extreme events, downscaling comparisons now commonly assess methods in terms of climate extremes, but hydrologic extremes are less well explored. Here, we test the ability of gridded downscaling models to replicate historical properties of climate and hydrologic extremes, as measured in terms of temporal sequencing (i.e. correlation tests) and distributional properties (i.e. tests for equality of probability distributions). Outputs from seven downscaling methods - bias correction constructed analogues (BCCA), double BCCA (DBCCA), BCCA with quantile mapping reordering (BCCAQ), bias correction spatial disaggregation (BCSD), BCSD using minimum/maximum temperature (BCSDX), the climate imprint delta method (CI), and bias corrected CI (BCCI) - are used to drive the Variable Infiltration Capacity (VIC) model over the snow-dominated Peace River basin, British Columbia. Outputs are tested using split-sample validation on 26 climate extremes indices (ClimDEX) and two hydrologic extremes indices (3-day peak flow and 7-day peak flow). To characterize observational uncertainty, four atmospheric reanalyses are used as climate model surrogates and two gridded observational data sets are used as downscaling target data. The skill of the downscaling methods generally depended on reanalysis and gridded observational data set. However, CI failed to reproduce the distribution and BCSD and BCSDX the timing of winter 7-day low-flow events, regardless of reanalysis or observational data set. Overall, DBCCA passed the greatest number of tests for the ClimDEX indices, while BCCAQ, which is designed to more accurately resolve event-scale spatial gradients, passed the greatest number of tests for hydrologic extremes. Non-stationarity in the observational/reanalysis data sets complicated the evaluation of downscaling performance. Comparing temporal homogeneity and trends in climate indices and hydrological model outputs calculated from downscaled reanalyses and gridded observations was useful for diagnosing the reliability of the various historical data sets. We recommend that such analyses be conducted before such data are used to construct future hydro-climatic change scenarios.
High-resolution distributed temperature sensing with the multiphoton-timing technique
NASA Astrophysics Data System (ADS)
Höbel, M.; Ricka, J.; Wüthrich, M.; Binkert, Th.
1995-06-01
We report on a multiphoton-timing distributed temperature sensor (DTS) based on the concept of distributed anti-Stokes Raman thermometry. The sensor combines the advantage of very high spatial resolution (40 cm) with moderate measurement times. In 5 min it is possible to determine the temperature of as many as 4000 points along an optical fiber with an accuracy Delta T less than 2 deg C. The new feature of the DTS system is the combination of a fast single-photon avalanche diode with specially designed real-time signal-processing electronics. We discuss various parameters that affect the operation of analog and photon-timing DTS systems. Particular emphasis is put on the consequences of the nonideal behavior of sensor components and the corresponding correction procedures.
Model-based aberration correction in a closed-loop wavefront-sensor-less adaptive optics system.
Song, H; Fraanje, R; Schitter, G; Kroese, H; Vdovin, G; Verhaegen, M
2010-11-08
In many scientific and medical applications, such as laser systems and microscopes, wavefront-sensor-less (WFSless) adaptive optics (AO) systems are used to improve the laser beam quality or the image resolution by correcting the wavefront aberration in the optical path. The lack of direct wavefront measurement in WFSless AO systems imposes a challenge to achieve efficient aberration correction. This paper presents an aberration correction approach for WFSlss AO systems based on the model of the WFSless AO system and a small number of intensity measurements, where the model is identified from the input-output data of the WFSless AO system by black-box identification. This approach is validated in an experimental setup with 20 static aberrations having Kolmogorov spatial distributions. By correcting N=9 Zernike modes (N is the number of aberration modes), an intensity improvement from 49% of the maximum value to 89% has been achieved in average based on N+5=14 intensity measurements. With the worst initial intensity, an improvement from 17% of the maximum value to 86% has been achieved based on N+4=13 intensity measurements.
Fletcher, E; Carmichael, O; Decarli, C
2012-01-01
We propose a template-based method for correcting field inhomogeneity biases in magnetic resonance images (MRI) of the human brain. At each algorithm iteration, the update of a B-spline deformation between an unbiased template image and the subject image is interleaved with estimation of a bias field based on the current template-to-image alignment. The bias field is modeled using a spatially smooth thin-plate spline interpolation based on ratios of local image patch intensity means between the deformed template and subject images. This is used to iteratively correct subject image intensities which are then used to improve the template-to-image deformation. Experiments on synthetic and real data sets of images with and without Alzheimer's disease suggest that the approach may have advantages over the popular N3 technique for modeling bias fields and narrowing intensity ranges of gray matter, white matter, and cerebrospinal fluid. This bias field correction method has the potential to be more accurate than correction schemes based solely on intrinsic image properties or hypothetical image intensity distributions.
Fletcher, E.; Carmichael, O.; DeCarli, C.
2013-01-01
We propose a template-based method for correcting field inhomogeneity biases in magnetic resonance images (MRI) of the human brain. At each algorithm iteration, the update of a B-spline deformation between an unbiased template image and the subject image is interleaved with estimation of a bias field based on the current template-to-image alignment. The bias field is modeled using a spatially smooth thin-plate spline interpolation based on ratios of local image patch intensity means between the deformed template and subject images. This is used to iteratively correct subject image intensities which are then used to improve the template-to-image deformation. Experiments on synthetic and real data sets of images with and without Alzheimer’s disease suggest that the approach may have advantages over the popular N3 technique for modeling bias fields and narrowing intensity ranges of gray matter, white matter, and cerebrospinal fluid. This bias field correction method has the potential to be more accurate than correction schemes based solely on intrinsic image properties or hypothetical image intensity distributions. PMID:23365843
Carrier-phase multipath corrections for GPS-based satellite attitude determination
NASA Technical Reports Server (NTRS)
Axelrad, A.; Reichert, P.
2001-01-01
This paper demonstrates the high degree of spatial repeatability of these errors for a spacecraft environment and describes a correction technique, termed the sky map method, which exploits the spatial correlation to correct measurements and improve the accuracy of GPS-based attitude solutions.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Megeath, S. T.; Kryukova, E.; Gutermuth, R.
2016-01-15
We analyze the spatial distribution of dusty young stellar objects (YSOs) identified in the Spitzer Survey of the Orion Molecular clouds, augmenting these data with Chandra X-ray observations to correct for incompleteness in dense clustered regions. We also devise a scheme to correct for spatially varying incompleteness when X-ray data are not available. The local surface densities of the YSOs range from 1 pc{sup −2} to over 10,000 pc{sup −2}, with protostars tending to be in higher density regions. This range of densities is similar to other surveyed molecular clouds with clusters, but broader than clouds without clusters. By identifyingmore » clusters and groups as continuous regions with surface densities ≥10 pc{sup −2}, we find that 59% of the YSOs are in the largest cluster, the Orion Nebula Cluster (ONC), while 13% of the YSOs are found in a distributed population. A lower fraction of protostars in the distributed population is evidence that it is somewhat older than the groups and clusters. An examination of the structural properties of the clusters and groups shows that the peak surface densities of the clusters increase approximately linearly with the number of members. Furthermore, all clusters with more than 70 members exhibit asymmetric and/or highly elongated structures. The ONC becomes azimuthally symmetric in the inner 0.1 pc, suggesting that the cluster is only ∼2 Myr in age. We find that the star formation efficiency (SFE) of the Orion B cloud is unusually low, and that the SFEs of individual groups and clusters are an order of magnitude higher than those of the clouds. Finally, we discuss the relationship between the young low mass stars in the Orion clouds and the Orion OB 1 association, and we determine upper limits to the fraction of disks that may be affected by UV radiation from OB stars or dynamical interactions in dense, clustered regions.« less
[Correction of light refraction and reflection in medical transmission optical tomography].
Tereshchenko, S A; Potapov, D A
2002-01-01
The effects of light refraction and reflection on the quality of image reconstruction in medical transmission optical tomography of high-scattering media are considered. It has been first noted that light refraction not only distorts the geometric scheme of measurements, but may lead to the appearance of object areas that cannot be scanned. Some ways of decreasing the effect of refraction on the reconstruction of spatial distribution of the extinction coefficient are stated.
Investigation of water imbibition in porous stone by thermal neutron radiography
NASA Astrophysics Data System (ADS)
Hassanein, R.; Meyer, H. O.; Carminati, A.; Estermann, M.; Lehmann, E.; Vontobel, P.
2006-10-01
The understanding and modelling of the process of water imbibition is important for various applications of physics (e.g. building or soil physics). To measure the spatial distribution of the water content at arbitrary times is not trivial. Neutron radiography provides an appropriate tool for such investigations with excellent time and spatial resolution. Because of the high sensitivity to hydrogen, even small amounts of water in a porous structure can be detected in samples with dimensions up to 40 cm. Three different porous stones found in Indiana, USA, have been investigated (Mansfield sandstone, Salem limestone and Hindustan whetstone). The imbibition of deionized water and a NaCl solution in up- and downwards directions has been tracked during several hours and radiographed at regular intervals. A correction method to reduce the disturbing effects due to neutron scattering is applied. This allows a quantitative evaluation of the water content in addition to the visualization of the water distribution. The results agree well with theoretical models describing water infiltration and reproduce the water content with a pixel resolution of 272 µm in time steps of 1 min. The comparison with the radiographed structure of the dry stone explains variations in the conduction or retention of the water, respectively. The experimental and correction procedures described here can be applied to other porous media and their uptake and loss of fluids.
Library based x-ray scatter correction for dedicated cone beam breast CT
Shi, Linxi; Karellas, Andrew; Zhu, Lei
2016-01-01
Purpose: The image quality of dedicated cone beam breast CT (CBBCT) is limited by substantial scatter contamination, resulting in cupping artifacts and contrast-loss in reconstructed images. Such effects obscure the visibility of soft-tissue lesions and calcifications, which hinders breast cancer detection and diagnosis. In this work, we propose a library-based software approach to suppress scatter on CBBCT images with high efficiency, accuracy, and reliability. Methods: The authors precompute a scatter library on simplified breast models with different sizes using the geant4-based Monte Carlo (MC) toolkit. The breast is approximated as a semiellipsoid with homogeneous glandular/adipose tissue mixture. For scatter correction on real clinical data, the authors estimate the breast size from a first-pass breast CT reconstruction and then select the corresponding scatter distribution from the library. The selected scatter distribution from simplified breast models is spatially translated to match the projection data from the clinical scan and is subtracted from the measured projection for effective scatter correction. The method performance was evaluated using 15 sets of patient data, with a wide range of breast sizes representing about 95% of general population. Spatial nonuniformity (SNU) and contrast to signal deviation ratio (CDR) were used as metrics for evaluation. Results: Since the time-consuming MC simulation for library generation is precomputed, the authors’ method efficiently corrects for scatter with minimal processing time. Furthermore, the authors find that a scatter library on a simple breast model with only one input parameter, i.e., the breast diameter, sufficiently guarantees improvements in SNU and CDR. For the 15 clinical datasets, the authors’ method reduces the average SNU from 7.14% to 2.47% in coronal views and from 10.14% to 3.02% in sagittal views. On average, the CDR is improved by a factor of 1.49 in coronal views and 2.12 in sagittal views. Conclusions: The library-based scatter correction does not require increase in radiation dose or hardware modifications, and it improves over the existing methods on implementation simplicity and computational efficiency. As demonstrated through patient studies, the authors’ approach is effective and stable, and is therefore clinically attractive for CBBCT imaging. PMID:27487870
NASA Astrophysics Data System (ADS)
Rebolledo Coy, M. A.; Villanueva, O. M. B.; Bartz-Beielstein, T.; Ribbe, L.
2017-12-01
Rainfall measurement plays an important role on the understanding and modeling of the water cycle. However, the assessment of scarce data regions using common rain gauge information, cannot be done using a straightforward approach. Some of the main problems concerning rainfall assessment are; the lack of a sufficiently dense grid of ground stations in extensive areas and the unstable spatial accuracy of the Satellite Rainfall Estimates (SREs). Following previous works on SREs analysis and bias-correction, we generate an ensemble model that corrects the bias error on a seasonal and yearly basis using six different state-of-the-art SREs (TRMM 3B42RT, TRMM 3B42v7, PERSIANN-CDR, CHIRPSv2, CMORPH and MSWEPv1.2) in a point-to-pixel approach for the studied period (2003-2015). Three different basins; Magdalena in Colombia, Imperial in Chile and Paraiba do Sul in Brazil are evaluated. Using Gaussian process regression and Bayesian robust regression we model the behavior of the ground stations and evaluate its goodness-of-fit by using the modified Kling-Gupta efficiency (KGE'). Following this evaluation, the models are re-fitted by taking into account the error distribution in each point and the corresponding KGE' is evaluated again. Both models were specified using the probabilistic language STAN. To improve the efficiency of the Gaussian model a clustering of the data was implemented. We also compared the performance of both models in term of uncertainty and stability against the raw input concluding that both models represent better the study areas. The results show that the error displays an exponential behavior for days where precipitation was present, this allows the models to be corrected according to the observed rainfall values. The seasonal evaluations also show improved performance in relation to the yearly evaluations. The use of bias-corrected SREs for hydrologic purposes in scarce data regions is highly recommended in order to merge the punctual values from the ground measurements and the spatial distribution of rainfall from the satellite estimates.
NASA Astrophysics Data System (ADS)
Jayasekera, D. L.; Kaluarachchi, J.; Kim, U.
2011-12-01
Rural river basins with sufficient water availability to maintain economic livelihoods can be affected with seasonal fluctuations of precipitation and sometimes by droughts. In addition, climate change impacts can also alter future water availability. General Circulation Models (GCMs) provide credible quantitative estimates of future climate conditions but such estimates are often characterized by bias and coarse scale resolution making it necessary to downscale the outputs for use in regional hydrologic models. This study develops a methodology to downscale and project future monthly precipitation in moderate scale basins where data are limited. A stochastic framework for single-site and multi-site generation of weekly rainfall is developed while preserving the historical temporal and spatial correlation structures. The spatial correlations in the simulated occurrences and the amounts are induced using spatially correlated yet serially independent random numbers. This method is applied to generate weekly precipitation data for a 100-year period in the Nam Ngum River Basin (NNRB) that has a land area of 16,780 km2 located in Lao P.D.R. This method is developed and applied using precipitation data from 1961 to 2000 for 10 selected weather stations that represents the basin rainfall characteristics. Bias-correction method, based on fitted theoretical probability distribution transformations, is applied to improve monthly mean frequency, intensity and the amount of raw GCM precipitation predicted at a given weather station using CGCM3.1 and ECHAM5 for SRES A2 emission scenario. Bias-correction procedure adjusts GCM precipitation to approximate the long-term frequency and the intensity distribution observed at a given weather station. Index of agreement and mean absolute error are determined to assess the overall ability and performance of the bias correction method. The generated precipitation series aggregated at monthly time step was perturbed by the change factors estimated using the corrected GCM and baseline scenarios for future time periods of 2011-2050 and 2051-2090. A network based hydrologic and water resources model, WEAP, was used to simulate the current water allocation and management practices to identify the impacts of climate change in the 20th century. The results of this work are used to identify the multiple challenges faced by stakeholders and planners in water allocation for competing demands in the presence of climate change impacts.
Women match men when learning a spatial skill.
Spence, Ian; Yu, Jingjie Jessica; Feng, Jing; Marshman, Jeff
2009-07-01
Meta-analytic studies have concluded that although training improves spatial cognition in both sexes, the male advantage generally persists. However, because some studies run counter to this pattern, a closer examination of the anomaly is warranted. The authors investigated the acquisition of a basic skill (spatial selective attention) using a matched-pair two-wave longitudinal design. Participants were screened with the use of an attentional visual field task, with the objective of selecting and matching 10 male-female pairs, over a wide range (30% to 57% correct). Subsequently, 20 participants 17-23 years of age (selected from 43 screened) were trained for 10 hr (distributed over several sessions) by playing a first-person shooter video game. This genre is known to be highly effective in enhancing spatial skills. All 20 participants improved, with matched members of the male-female pairs achieving very similar gains, independent of starting level. This is consistent with the hypothesis that the learning trajectory of women is not inferior to that of men when acquiring a basic spatial skill. Training methods that develop basic spatial skills may be essential to achieve gender parity in both basic and complex spatial tasks.
NASA Astrophysics Data System (ADS)
Meyer, Michael; Kalender, Willi A.; Kyriakou, Yiannis
2010-01-01
Scattered radiation is a major source of artifacts in flat detector computed tomography (FDCT) due to the increased irradiated volumes. We propose a fast projection-based algorithm for correction of scatter artifacts. The presented algorithm combines a convolution method to determine the spatial distribution of the scatter intensity distribution with an object-size-dependent scaling of the scatter intensity distributions using a priori information generated by Monte Carlo simulations. A projection-based (PBSE) and an image-based (IBSE) strategy for size estimation of the scanned object are presented. Both strategies provide good correction and comparable results; the faster PBSE strategy is recommended. Even with such a fast and simple algorithm that in the PBSE variant does not rely on reconstructed volumes or scatter measurements, it is possible to provide a reasonable scatter correction even for truncated scans. For both simulations and measurements, scatter artifacts were significantly reduced and the algorithm showed stable behavior in the z-direction. For simulated voxelized head, hip and thorax phantoms, a figure of merit Q of 0.82, 0.76 and 0.77 was reached, respectively (Q = 0 for uncorrected, Q = 1 for ideal). For a water phantom with 15 cm diameter, for example, a cupping reduction from 10.8% down to 2.1% was achieved. The performance of the correction method has limitations in the case of measurements using non-ideal detectors, intensity calibration, etc. An iterative approach to overcome most of these limitations was proposed. This approach is based on root finding of a cupping metric and may be useful for other scatter correction methods as well. By this optimization, cupping of the measured water phantom was further reduced down to 0.9%. The algorithm was evaluated on a commercial system including truncated and non-homogeneous clinically relevant objects.
Spatial frequency spectrum of the x-ray scatter distribution in CBCT projections
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bootsma, G. J.; Verhaegen, F.; Department of Oncology, Medical Physics Unit, McGill University, Montreal, Quebec H3G 1A4
2013-11-15
Purpose: X-ray scatter is a source of significant image quality loss in cone-beam computed tomography (CBCT). The use of Monte Carlo (MC) simulations separating primary and scattered photons has allowed the structure and nature of the scatter distribution in CBCT to become better elucidated. This work seeks to quantify the structure and determine a suitable basis function for the scatter distribution by examining its spectral components using Fourier analysis.Methods: The scatter distribution projection data were simulated using a CBCT MC model based on the EGSnrc code. CBCT projection data, with separated primary and scatter signal, were generated for a 30.6more » cm diameter water cylinder [single angle projection with varying axis-to-detector distance (ADD) and bowtie filters] and two anthropomorphic phantoms (head and pelvis, 360 projections sampled every 1°, with and without a compensator). The Fourier transform of the resulting scatter distributions was computed and analyzed both qualitatively and quantitatively. A novel metric called the scatter frequency width (SFW) is introduced to determine the scatter distribution's frequency content. The frequency content results are used to determine a set basis functions, consisting of low-frequency sine and cosine functions, to fit and denoise the scatter distribution generated from MC simulations using a reduced number of photons and projections. The signal recovery is implemented using Fourier filtering (low-pass Butterworth filter) and interpolation. Estimates of the scatter distribution are used to correct and reconstruct simulated projections.Results: The spatial and angular frequencies are contained within a maximum frequency of 0.1 cm{sup −1} and 7/(2π) rad{sup −1} for the imaging scenarios examined, with these values varying depending on the object and imaging setup (e.g., ADD and compensator). These data indicate spatial and angular sampling every 5 cm and π/7 rad (∼25°) can be used to properly capture the scatter distribution, with reduced sampling possible depending on the imaging scenario. Using a low-pass Butterworth filter, tuned with the SFW values, to denoise the scatter projection data generated from MC simulations using 10{sup 6} photons resulted in an error reduction of greater than 85% for the estimating scatter in single and multiple projections. Analysis showed that the use of a compensator helped reduce the error in estimating the scatter distribution from limited photon simulations by more than 37% when compared to the case without a compensator for the head and pelvis phantoms. Reconstructions of simulated head phantom projections corrected by the filtered and interpolated scatter estimates showed improvements in overall image quality.Conclusions: The spatial frequency content of the scatter distribution in CBCT is found to be contained within the low frequency domain. The frequency content is modulated both by object and imaging parameters (ADD and compensator). The low-frequency nature of the scatter distribution allows for a limited set of sine and cosine basis functions to be used to accurately represent the scatter signal in the presence of noise and reduced data sampling decreasing MC based scatter estimation time. Compensator induced modulation of the scatter distribution reduces the frequency content and improves the fitting results.« less
Pressure-Sensitive Paint Measurements on Surfaces with Non-Uniform Temperature
NASA Technical Reports Server (NTRS)
Bencic, Timothy J.
1999-01-01
Pressure-sensitive paint (PSP) has become a useful tool to augment conventional pressure taps in measuring the surface pressure distribution of aerodynamic components in wind tunnel testing. While the PSP offers the advantage of a non-intrusive global mapping of the surface pressure, one prominent drawback to the accuracy of this technique is the inherent temperature sensitivity of the coating's luminescent intensity. A typical aerodynamic surface PSP test has relied on the coated surface to be both spatially and temporally isothermal, along with conventional instrumentation for an in situ calibration to generate the highest accuracy pressure mappings. In some tests however, spatial and temporal thermal gradients are generated by the nature of the test as in a blowing jet impinging on a surface. In these cases, the temperature variations on the painted surface must be accounted for in order to yield high accuracy and reliable data. A new temperature correction technique was developed at NASA Lewis to collapse a "family" of PSP calibration curves to a single intensity ratio versus pressure curve. This correction allows a streamlined procedure to be followed whether or not temperature information is used in the data reduction of the PSP. This paper explores the use of conventional instrumentation such as thermocouples and pressure taps along with temperature-sensitive paint (TSP) to correct for the thermal gradients that exist in aeropropulsion PSP tests. Temperature corrected PSP measurements for both a supersonic mixer ejector and jet cavity interaction tests are presented.
NASA Astrophysics Data System (ADS)
Chimot, Julien; Pepijn Veefkind, J.; Vlemmix, Tim; Levelt, Pieternel F.
2018-04-01
A global picture of atmospheric aerosol vertical distribution with a high temporal resolution is of key importance not only for climate, cloud formation, and air quality research studies but also for correcting scattered radiation induced by aerosols in absorbing trace gas retrievals from passive satellite sensors. Aerosol layer height (ALH) was retrieved from the OMI 477 nm O2 - O2 band and its spatial pattern evaluated over selected cloud-free scenes. Such retrievals benefit from a synergy with MODIS data to provide complementary information on aerosols and cloudy pixels. We used a neural network approach previously trained and developed. Comparison with CALIOP aerosol level 2 products over urban and industrial pollution in eastern China shows consistent spatial patterns with an uncertainty in the range of 462-648 m. In addition, we show the possibility to determine the height of thick aerosol layers released by intensive biomass burning events in South America and Russia from OMI visible measurements. A Saharan dust outbreak over sea is finally discussed. Complementary detailed analyses show that the assumed aerosol properties in the forward modelling are the key factors affecting the accuracy of the results, together with potential cloud residuals in the observation pixels. Furthermore, we demonstrate that the physical meaning of the retrieved ALH scalar corresponds to the weighted average of the vertical aerosol extinction profile. These encouraging findings strongly suggest the potential of the OMI ALH product, and in more general the use of the 477 nm O2 - O2 band from present and future similar satellite sensors, for climate studies as well as for future aerosol correction in air quality trace gas retrievals.
NASA Astrophysics Data System (ADS)
Kienzle, Stefan
2015-04-01
Precipitation is the central driving force of most hydrological processes, and is also the most variable element of the hydrological cycle. As the precipitation to runoff ratio is non-linear, errors in precipitation estimations are amplified in streamflow simulations. Therefore, the accurate estimate of areal precipitation is essential for watershed models and relevant impacts studies. A procedure is presented to demonstrate the spatial distribution of daily precipitation and temperature estimates across the Rocky Mountains within the framework of the ACRU agro-hydrological modelling system (ACRU). ACRU (Schulze, 1995) is a physical-conceptual, semi-distributed hydrological modelling system designed to be responsive to changes in land use and climate. The model has been updated to include specific high-mountain and cold climate routines and is applied to simulate impacts of land cover and climate change on the hydrological behaviour of numerous Rocky Mountain watersheds in Alberta, Canada. Both air temperature and precipitation time series need to be downscaled to hydrological response units (HRUs), as they are the spatial modelling units for the model. The estimation of accurate daily air temperatures is critical for the separation of rain and snow. The precipitation estimation procedure integrates a spatially distributed daily precipitation database for the period 1950 to 2010 at a scale of 10 by 10 km with a 1971-2000 climate normal database available at 2 by 2 km (PRISM). Resulting daily precipitation time series are further downscaled to the spatial resolution of hydrological response units, defined by 100 m elevation bands, land cover, and solar radiation, which have an average size of about 15 km2. As snow measurements are known to have a potential under-catch of up to 40%, further adjustment of snowfall may need to be increased using a procedure by Richter (1995). Finally, precipitation input to HRUs with slopes steeper than 10% need to be further corrected, because the true, sloped area, has a larger area than the planimetric area derived from a GIS. The omission of correcting for sloped areas would result in incorrect calculations of interception volumes, soil moisture storages, groundwater recharge rates, actual evapotranspiration volumes, and runoff coefficients. Daily minimum and maximum air temperatures are estimated for each HRU by downscaling the 10km time series to the HRUs by (a) applying monthly mean lapse rates, estimated either from surrounding climate stations or from the PRISM climate normal dataset in combination with a digital elevation model, (b) adjusting further for aspect of the HRU based on monthly mean incoming solar radiation, and (c) adjusting for canopy cover using the monthly mean leaf area indices. Precipitation estimates can be verified using independent snow water equivalent measurements derived from snow pillow or snow course observations, while temperature estimates are verified against either independent temperature measurements from climate stations, or from fire observation towers.
NASA Astrophysics Data System (ADS)
Wang, Jinliang; Wu, Xuejiao
2010-11-01
Geometric correction of imagery is a basic application of remote sensing technology. Its precision will impact directly on the accuracy and reliability of applications. The accuracy of geometric correction depends on many factors, including the used model for correction and the accuracy of the reference map, the number of ground control points (GCP) and its spatial distribution, resampling methods. The ETM+ image of Kunming Dianchi Lake Basin and 1:50000 geographical maps had been used to compare different correction methods. The results showed that: (1) The correction errors were more than one pixel and some of them were several pixels when the polynomial model was used. The correction accuracy was not stable when the Delaunay model was used. The correction errors were less than one pixel when the collinearity equation was used. (2) 6, 9, 25 and 35 GCP were selected randomly for geometric correction using the polynomial correction model respectively, the best result was obtained when 25 GCPs were used. (3) The contrast ratio of image corrected by using nearest neighbor and the best resampling rate was compared to that of using the cubic convolution and bilinear model. But the continuity of pixel gravy value was not very good. The contrast of image corrected was the worst and the computation time was the longest by using the cubic convolution method. According to the above results, the result was the best by using bilinear to resample.
Can we improve streamflow simulation by using higher resolution rainfall information?
NASA Astrophysics Data System (ADS)
Lobligeois, Florent; Andréassian, Vazken; Perrin, Charles
2013-04-01
The catchment response to rainfall is the interplay between space-time variability of precipitation, catchment characteristics and antecedent hydrological conditions. Precipitation dominates the high frequency hydrological response, and its simulation is thus dependent on the way rainfall is represented. One of the characteristics which distinguishes distributed from lumped models is their ability to represent explicitly the spatial variability of precipitation and catchment characteristics. The sensitivity of runoff hydrographs to the spatial variability of forcing data has been a major concern of researchers over the last three decades. However, although the literature on the relationship between spatial rainfall and runoff response is abundant, results are contrasted and sometimes contradictory. Several studies concluded that including information on rainfall spatial distribution improves discharge simulation (e.g. Ajami et al., 2004, among others) whereas other studies showed the lack of significant improvement in simulations with better information on rainfall spatial pattern (e.g. Andréassian et al., 2004, among others). The difficulties to reach a clear consensus is mainly due to the fact that each modeling study is implemented only on a few catchments whereas the impact of the spatial distribution of rainfall on runoff is known to be catchment and event characteristics-dependent. Many studies are virtual experiments and only compare flow simulations, which makes it difficult to reach conclusions transposable to real-life case studies. Moreover, the hydrological rainfall-runoff models differ between the studies and the parameterization strategies sometimes tend to advantage the distributed approach (or the lumped one). Recently, Météo-France developed a rainfall reanalysis over the whole French territory at the 1-kilometer resolution and the hourly time step over a 10-year period combining radar data and raingauge measurements: weather radar data were corrected and adjusted with both hourly and daily raingauge data. Based on this new high resolution product, we propose a framework to evaluate the improvements in streamflow simulation by using higher resolution rainfall information. Semi-distributed modelling is performed for different spatial resolution of precipitation forcing: from lumped to semi-distributed simulations. Here we do not work on synthetic (simulated) streamflow, but with actual measurements, on a large set of 181 French catchments representing a variety of size and climate. The rainfall-runoff model is re-calibrated for each resolution of rainfall spatial distribution over a 5-year sub-period and evaluated on the complementary sub-period in validation mode. The results are analysed by catchment classes based on catchment area and for various types of rainfall events based on the spatial variability of precipitation. References Ajami, N. K., Gupta, H. V, Wagener, T. & Sorooshian, S. (2004) Calibration of a semi-distributed hydrologic model for streamflow estimation along a river system. Journal of Hydrology 298(1-4), 112-135. Andréassian, V., Oddos, A., Michel, C., Anctil, F., Perrin, C. & Loumagne, C. (2004) Impact of spatial aggregation of inputs and parameters on the efficiency of rainfall-runoff models: A theoretical study using chimera watersheds. Water Resources Research 40(5), 1-9.
Water quality modeling in the dead end sections of drinking water distribution networks.
Abokifa, Ahmed A; Yang, Y Jeffrey; Lo, Cynthia S; Biswas, Pratim
2016-02-01
Dead-end sections of drinking water distribution networks are known to be problematic zones in terms of water quality degradation. Extended residence time due to water stagnation leads to rapid reduction of disinfectant residuals allowing the regrowth of microbial pathogens. Water quality models developed so far apply spatial aggregation and temporal averaging techniques for hydraulic parameters by assigning hourly averaged water demands to the main nodes of the network. Although this practice has generally resulted in minimal loss of accuracy for the predicted disinfectant concentrations in main water transmission lines, this is not the case for the peripheries of the distribution network. This study proposes a new approach for simulating disinfectant residuals in dead end pipes while accounting for both spatial and temporal variability in hydraulic and transport parameters. A stochastic demand generator was developed to represent residential water pulses based on a non-homogenous Poisson process. Dispersive solute transport was considered using highly dynamic dispersion rates. A genetic algorithm was used to calibrate the axial hydraulic profile of the dead-end pipe based on the different demand shares of the withdrawal nodes. A parametric sensitivity analysis was done to assess the model performance under variation of different simulation parameters. A group of Monte-Carlo ensembles was carried out to investigate the influence of spatial and temporal variations in flow demands on the simulation accuracy. A set of three correction factors were analytically derived to adjust residence time, dispersion rate and wall demand to overcome simulation error caused by spatial aggregation approximation. The current model results show better agreement with field-measured concentrations of conservative fluoride tracer and free chlorine disinfectant than the simulations of recent advection dispersion reaction models published in the literature. Accuracy of the simulated concentration profiles showed significant dependence on the spatial distribution of the flow demands compared to temporal variation. Copyright © 2015 Elsevier Ltd. All rights reserved.
Harnish, Roy; Prevrhal, Sven; Alavi, Abass; Zaidi, Habib; Lang, Thomas F
2014-07-01
To determine if metal artefact reduction (MAR) combined with a priori knowledge of prosthesis material composition can be applied to obtain CT-based attenuation maps with sufficient accuracy for quantitative assessment of (18)F-fluorodeoxyglucose uptake in lesions near metallic prostheses. A custom hip prosthesis phantom with a lesion-sized cavity filled with 0.2 ml (18)F-FDG solution having an activity of 3.367 MBq adjacent to a prosthesis bore was imaged twice with a chrome-cobalt steel hip prosthesis and a plastic replica, respectively. Scanning was performed on a clinical hybrid PET/CT system equipped with an additional external (137)Cs transmission source. PET emission images were reconstructed from both phantom configurations with CT-based attenuation correction (CTAC) and with CT-based attenuation correction using MAR (MARCTAC). To compare results with the attenuation-correction method extant prior to the advent of PET/CT, we also carried out attenuation correction with (137)Cs transmission-based attenuation correction (TXAC). CTAC and MARCTAC images were scaled to attenuation coefficients at 511 keV using a trilinear function that mapped the highest CT values to the prosthesis alloy attenuation coefficient. Accuracy and spatial distribution of the lesion activity was compared between the three reconstruction schemes. Compared to the reference activity of 3.37 MBq, the estimated activity quantified from the PET image corrected by TXAC was 3.41 MBq. The activity estimated from PET images corrected by MARCTAC was similar in accuracy at 3.32 MBq. CTAC corrected PET images resulted in nearly 40 % overestimation of lesion activity at 4.70 MBq. Comparison of PET images obtained with the plastic and metal prostheses in place showed that CTAC resulted in a marked distortion of the (18)F-FDG distribution within the lesion, whereas application of MARCTAC and TXAC resulted in lesion distributions similar to those observed with the plastic replica. MAR combined with a trilinear CT number mapping for PET attenuation correction resulted in estimates of lesion activity comparable in accuracy to that obtained with (137)Cs transmission-based attenuation correction, and far superior to estimates made without attenuation correction or with a standard CT attenuation map. The ability to use CT images for attenuation correction is a potentially important development because it obviates the need for a (137)Cs transmission source, which entails extra scan time, logistical complexity and expense.
NASA Technical Reports Server (NTRS)
Tsang, Leung; Hwang, Jenq-Neng
1996-01-01
A method to incorporate passive microwave remote sensing measurements within a spatially distributed snow hydrology model to provide estimates of the spatial distribution of Snow Water Equivalent (SWE) as a function of time is implemented. The passive microwave remote sensing measurements are at 25 km resolution. However, in mountain regions the spatial variability of SWE over a 25 km footprint is large due to topographic influences. On the other hand, the snow hydrology model has built-in topographic information and the capability to estimate SWE at a 1 km resolution. In our work, the snow hydrology SWE estimates are updated and corrected using SSM/I passive microwave remote sensing measurements. The method is applied to the Upper Rio Grande River Basin in the mountains of Colorado. The change in prediction of SWE from hydrology modeling with and without updating is compared with measurements from two SNOTEL sites in and near the basin. The results indicate that the method incorporating the remote sensing measurements into the hydrology model is able to more closely estimate the temporal evolution of the measured values of SWE as a function of time.
NASA Astrophysics Data System (ADS)
Gruneisen, Mark T.; Sickmiller, Brett A.; Flanagan, Michael B.; Black, James P.; Stoltenberg, Kurt E.; Duchane, Alexander W.
2016-02-01
Spatial filtering is an important technique for reducing sky background noise in a satellite quantum key distribution downlink receiver. Atmospheric turbulence limits the extent to which spatial filtering can reduce sky noise without introducing signal losses. Using atmospheric propagation and compensation simulations, the potential benefit of adaptive optics (AO) to secure key generation (SKG) is quantified. Simulations are performed assuming optical propagation from a low-Earth-orbit satellite to a terrestrial receiver that includes AO. Higher-order AO correction is modeled assuming a Shack-Hartmann wavefront sensor and a continuous-face-sheet deformable mirror. The effects of atmospheric turbulence, tracking, and higher-order AO on the photon capture efficiency are simulated using statistical representations of turbulence and a time-domain wave-optics hardware emulator. SKG rates are calculated for a decoy-state protocol as a function of the receiver field of view for various strengths of turbulence, sky radiances, and pointing angles. The results show that at fields of view smaller than those discussed by others, AO technologies can enhance SKG rates in daylight and enable SKG where it would otherwise be prohibited as a consequence of background optical noise and signal loss due to propagation and turbulence effects.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Batiste, Merida; Bentz, Misty C.; Manne-Nicholas, Emily R.
We present new bulge stellar velocity dispersion measurements for 10 active galaxies with secure M {sub BH} determinations from reverberation mapping. These new velocity dispersion measurements are based on spatially resolved kinematics from integral-field (IFU) spectroscopy. In all but one case, the field of view of the IFU extends beyond the effective radius of the galaxy, and in the case of Mrk 79 it extends to almost one half the effective radius. This combination of spatial resolution and field of view allows for secure determinations of stellar velocity dispersion within the effective radius for all 10 target galaxies. Spatially resolvedmore » maps of the first ( V ) and second ( σ {sub ⋆}) moments of the line of sight velocity distribution indicate the presence of kinematic substructure in most cases. In future projects we plan to explore methods of correcting for the effects of kinematic substructure in the derived bulge stellar velocity dispersion measurements.« less
NASA Astrophysics Data System (ADS)
Batiste, Merida; Bentz, Misty C.; Manne-Nicholas, Emily R.; Onken, Christopher A.; Bershady, Matthew A.
2017-02-01
We present new bulge stellar velocity dispersion measurements for 10 active galaxies with secure MBH determinations from reverberation mapping. These new velocity dispersion measurements are based on spatially resolved kinematics from integral-field (IFU) spectroscopy. In all but one case, the field of view of the IFU extends beyond the effective radius of the galaxy, and in the case of Mrk 79 it extends to almost one half the effective radius. This combination of spatial resolution and field of view allows for secure determinations of stellar velocity dispersion within the effective radius for all 10 target galaxies. Spatially resolved maps of the first (V) and second (σ⋆) moments of the line of sight velocity distribution indicate the presence of kinematic substructure in most cases. In future projects we plan to explore methods of correcting for the effects of kinematic substructure in the derived bulge stellar velocity dispersion measurements.
NASA Astrophysics Data System (ADS)
Atencia, A.; Llasat, M. C.; Garrote, L.; Mediero, L.
2010-10-01
The performance of distributed hydrological models depends on the resolution, both spatial and temporal, of the rainfall surface data introduced. The estimation of quantitative precipitation from meteorological radar or satellite can improve hydrological model results, thanks to an indirect estimation at higher spatial and temporal resolution. In this work, composed radar data from a network of three C-band radars, with 6-minutal temporal and 2 × 2 km2 spatial resolution, provided by the Catalan Meteorological Service, is used to feed the RIBS distributed hydrological model. A Window Probability Matching Method (gage-adjustment method) is applied to four cases of heavy rainfall to improve the observed rainfall sub-estimation in both convective and stratiform Z/R relations used over Catalonia. Once the rainfall field has been adequately obtained, an advection correction, based on cross-correlation between two consecutive images, was introduced to get several time resolutions from 1 min to 30 min. Each different resolution is treated as an independent event, resulting in a probable range of input rainfall data. This ensemble of rainfall data is used, together with other sources of uncertainty, such as the initial basin state or the accuracy of discharge measurements, to calibrate the RIBS model using probabilistic methodology. A sensitivity analysis of time resolutions was implemented by comparing the various results with real values from stream-flow measurement stations.
NASA Technical Reports Server (NTRS)
Herskovits, E. H.; Megalooikonomou, V.; Davatzikos, C.; Chen, A.; Bryan, R. N.; Gerring, J. P.
1999-01-01
PURPOSE: To determine whether there is an association between the spatial distribution of lesions detected at magnetic resonance (MR) imaging of the brain in children after closed-head injury and the development of secondary attention-deficit/hyperactivity disorder (ADHD). MATERIALS AND METHODS: Data obtained from 76 children without prior history of ADHD were analyzed. MR images were obtained 3 months after closed-head injury. After manual delineation of lesions, images were registered to the Talairach coordinate system. For each subject, registered images and secondary ADHD status were integrated into a brain-image database, which contains depiction (visualization) and statistical analysis software. Using this database, we assessed visually the spatial distributions of lesions and performed statistical analysis of image and clinical variables. RESULTS: Of the 76 children, 15 developed secondary ADHD. Depiction of the data suggested that children who developed secondary ADHD had more lesions in the right putamen than children who did not develop secondary ADHD; this impression was confirmed statistically. After Bonferroni correction, we could not demonstrate significant differences between secondary ADHD status and lesion burdens for the right caudate nucleus or the right globus pallidus. CONCLUSION: Closed-head injury-induced lesions in the right putamen in children are associated with subsequent development of secondary ADHD. Depiction software is useful in guiding statistical analysis of image data.
Assessment of three dead detector correction methods for cone-beam computed tomography
DOE Office of Scientific and Technical Information (OSTI.GOV)
Nelms, David W.; Shukla, Hemant I.; Nixon, Earl
Purpose: Dead detectors due to manufacturing defects or radiation damage in the electronic portal imaging devices (EPIDs) used for cone-beam computed tomography (CBCT) can lead to image degradation and ring artifacts. In this work three dead detector correction methods were assessed using megavoltage CBCT (MVCBCT) as a test system, with the goals of assessing the relative effectiveness of the three methods and establishing the conditions for which they fail. Methods: MVCBCT projections acquired with four linacs at 8 and 60 MU (monitor units) were degraded with varying percentages (2%-95%) of randomly distributed dead single detectors (RDSs), randomly distributed dead detectormore » clusters (RDCs) of 2 mm diameter, and nonrandomly distributed dead detector disks (NRDDs) of varying diameter (4-16 mm). Correction algorithms were bidirectional linear interpolation (BLI), quad-directional linear interpolation (QLI), and a Laplacian solution (LS) method. Correction method failure was defined to occur if ring artifacts were present in the reconstructed phantom images from any linac or if the modulation transfer function (MTF) for any linac dropped below baseline with a p value, calculated with the two sample t test, of less than 0.01. Results: All correction methods failed at the same or lower RDC/RDS percentages and NRDD diameters for the 60 MU as for the 8 MU cases. The LS method tended to outperform or match the BLI and QLI methods. If ring artifacts anywhere in the images were considered unacceptable, the LS method failed for 60 MU at >33% RDS, >2% RDC, and >4 mm NRDD. If ring artifacts within 4 mm longitudinally of the phantom section interfaces were considered acceptable, the LS method failed for 60 MU at >90% RDS, >80% RDC, and >4 mm NRDD. LS failed due to MTF drop for 60 MU at >50% RDS, >25% RDC, and >4 mm NRDD. Conclusions: The LS method is superior to the BLI and QLI methods, and correction algorithm effectiveness decreases as imaging dose increases. All correction methods failed first due to ring artifacts and second due to MTF drop. If ring artifacts in axial slices within a 4 mm longitudinal distance from phantom section interfaces are acceptable, statistically significant loss in spatial resolution does not occur until over 25% of the EPID is covered in randomly distributed dead detectors, or NRDDs of 4 mm diameter are present.« less
Deterministic error correction for nonlocal spatial-polarization hyperentanglement
Li, Tao; Wang, Guan-Yu; Deng, Fu-Guo; Long, Gui-Lu
2016-01-01
Hyperentanglement is an effective quantum source for quantum communication network due to its high capacity, low loss rate, and its unusual character in teleportation of quantum particle fully. Here we present a deterministic error-correction scheme for nonlocal spatial-polarization hyperentangled photon pairs over collective-noise channels. In our scheme, the spatial-polarization hyperentanglement is first encoded into a spatial-defined time-bin entanglement with identical polarization before it is transmitted over collective-noise channels, which leads to the error rejection of the spatial entanglement during the transmission. The polarization noise affecting the polarization entanglement can be corrected with a proper one-step decoding procedure. The two parties in quantum communication can, in principle, obtain a nonlocal maximally entangled spatial-polarization hyperentanglement in a deterministic way, which makes our protocol more convenient than others in long-distance quantum communication. PMID:26861681
Deterministic error correction for nonlocal spatial-polarization hyperentanglement.
Li, Tao; Wang, Guan-Yu; Deng, Fu-Guo; Long, Gui-Lu
2016-02-10
Hyperentanglement is an effective quantum source for quantum communication network due to its high capacity, low loss rate, and its unusual character in teleportation of quantum particle fully. Here we present a deterministic error-correction scheme for nonlocal spatial-polarization hyperentangled photon pairs over collective-noise channels. In our scheme, the spatial-polarization hyperentanglement is first encoded into a spatial-defined time-bin entanglement with identical polarization before it is transmitted over collective-noise channels, which leads to the error rejection of the spatial entanglement during the transmission. The polarization noise affecting the polarization entanglement can be corrected with a proper one-step decoding procedure. The two parties in quantum communication can, in principle, obtain a nonlocal maximally entangled spatial-polarization hyperentanglement in a deterministic way, which makes our protocol more convenient than others in long-distance quantum communication.
Remotely sensed soil moisture input to a hydrologic model
NASA Technical Reports Server (NTRS)
Engman, E. T.; Kustas, W. P.; Wang, J. R.
1989-01-01
The possibility of using detailed spatial soil moisture maps as input to a runoff model was investigated. The water balance of a small drainage basin was simulated using a simple storage model. Aircraft microwave measurements of soil moisture were used to construct two-dimensional maps of the spatial distribution of the soil moisture. Data from overflights on different dates provided the temporal changes resulting from soil drainage and evapotranspiration. The study site and data collection are described, and the soil measurement data are given. The model selection is discussed, and the simulation results are summarized. It is concluded that a time series of soil moisture is a valuable new type of data for verifying model performance and for updating and correcting simulated streamflow.
NASA Astrophysics Data System (ADS)
Murillo Feo, C. A.; Martnez Martinez, L. J.; Correa Muñoz, N. A.
2016-06-01
The accuracy of locating attributes on topographic surfaces when, using GPS in mountainous areas, is affected by obstacles to wave propagation. As part of this research on the semi-automatic detection of landslides, we evaluate the accuracy and spatial distribution of the horizontal error in GPS positioning in the tertiary road network of six municipalities located in mountainous areas in the department of Cauca, Colombia, using geo-referencing with GPS mapping equipment and static-fast and pseudo-kinematic methods. We obtained quality parameters for the GPS surveys with differential correction, using a post-processing method. The consolidated database underwent exploratory analyses to determine the statistical distribution, a multivariate analysis to establish relationships and partnerships between the variables, and an analysis of the spatial variability and calculus of accuracy, considering the effect of non-Gaussian distribution errors. The evaluation of the internal validity of the data provide metrics with a confidence level of 95% between 1.24 and 2.45 m in the static-fast mode and between 0.86 and 4.2 m in the pseudo-kinematic mode. The external validity had an absolute error of 4.69 m, indicating that this descriptor is more critical than precision. Based on the ASPRS standard, the scale obtained with the evaluated equipment was in the order of 1:20000, a level of detail expected in the landslide-mapping project. Modelling the spatial variability of the horizontal errors from the empirical semi-variogram analysis showed predictions errors close to the external validity of the devices.
Geographic expression of AIDS epidemic in Campinas, Southeastern Brazil, between 1980 and 2005.
Stephan, Celso; Henn, Carlos Alberto; Donalisio, Maria Rita
2010-10-01
To analyze the spatial distribution of reported AIDS cases in adults and its association with living conditions in the city of Campinas, Southeastern Brazil. Data on AIDS cases in men (n=2,945) and women (n=1,230) aged more than 13 years and living in Campinas, recorded in the SINAN (Brazilian Information System for Notifiable Diseases), were used to map the spatial distribution of this disease and the male:female ratio. Maps were constructed for the following periods: from 1980 to 1995, from 1996 to 2000, and from 2001 to 2005. The variables included in the analysis were address, sex and age. A weighted composite index was used to study living and health conditions in the area. Patients' home addresses were geocoded on a cartographic base, after correction and standardization according to a reference database of streets. A generalized additive model was adjusted to analyze the spatial distribution of the ratio of male:female cases in space, in the three study periods. The ratio of male:female cases was higher in areas with better living conditions (central) and around the prison (northwestern), where families of prisoners and former prisoners live temporarily, while this ratio was lower in the city suburbs (southwestern). The trends towards the AIDS epidemic affecting more women and poorer individuals were confirmed by the decrease in the ratio of male:female cases in the period, particularly in vulnerable and impoverished populations. Geographic information systems and spatial data analysis can be useful for AIDS control and surveillance actions.
Development of Spatiotemporal Bias-Correction Techniques for Downscaling GCM Predictions
NASA Astrophysics Data System (ADS)
Hwang, S.; Graham, W. D.; Geurink, J.; Adams, A.; Martinez, C. J.
2010-12-01
Accurately representing the spatial variability of precipitation is an important factor for predicting watershed response to climatic forcing, particularly in small, low-relief watersheds affected by convective storm systems. Although Global Circulation Models (GCMs) generally preserve spatial relationships between large-scale and local-scale mean precipitation trends, most GCM downscaling techniques focus on preserving only observed temporal variability on point by point basis, not spatial patterns of events. Downscaled GCM results (e.g., CMIP3 ensembles) have been widely used to predict hydrologic implications of climate variability and climate change in large snow-dominated river basins in the western United States (Diffenbaugh et al., 2008; Adam et al., 2009). However fewer applications to smaller rain-driven river basins in the southeastern US (where preserving spatial variability of rainfall patterns may be more important) have been reported. In this study a new method was developed to bias-correct GCMs to preserve both the long term temporal mean and variance of the precipitation data, and the spatial structure of daily precipitation fields. Forty-year retrospective simulations (1960-1999) from 16 GCMs were collected (IPCC, 2007; WCRP CMIP3 multi-model database: https://esg.llnl.gov:8443/), and the daily precipitation data at coarse resolution (i.e., 280km) were interpolated to 12km spatial resolution and bias corrected using gridded observations over the state of Florida (Maurer et al., 2002; Wood et al, 2002; Wood et al, 2004). In this method spatial random fields which preserved the observed spatial correlation structure of the historic gridded observations and the spatial mean corresponding to the coarse scale GCM daily rainfall were generated. The spatiotemporal variability of the spatio-temporally bias-corrected GCMs were evaluated against gridded observations, and compared to the original temporally bias-corrected and downscaled CMIP3 data for the central Florida. The hydrologic response of two southwest Florida watersheds to the gridded observation data, the original bias corrected CMIP3 data, and the new spatiotemporally corrected CMIP3 predictions was compared using an integrated surface-subsurface hydrologic model developed by Tampa Bay Water.
NASA Technical Reports Server (NTRS)
Lawton, Robert M.; Lawton, Robert O.
2010-01-01
Didymopanax pittieri is a common shade-intolerant tree colonizing treefall gaps in the elfin forests on windswept ridgecrests in the lower montane rain forests of the Cordillera de Tilarain, Costa Rica. All D. pittieri taller than > 0.5 m in a 5.2-ha elfin forested portion of a gridded study watershed in the Monteverde Cloud Forest Preserve were located, mapped, and measured. This local population of D. pittieri is spatially inhomogeneous, in that density increases with increasing wind exposure; D. pittieri are more abundant near ridge crests than lower on windward slopes. The important and ubiquitous phenomenon of spatial inhomogeneity in population density is addressed and corrected for in spatial analyses by the application of the inhomogeneous version of Ripley's K. The spatial patterns of four size classes of D. pittieri (<5 cm dbh, 5-10 cm dbh, 10-20 cm dbh, and> 20 cm dbh) were investigated. Within the large-scale trend in density driven by wind exposure, D. pittieri saplings are clumped at the scale of treefall gaps and at the scale of patches of aggregated gaps. D. pittieri 5-10 cm dbh are randomly distributed, apparently due to competitive thinning of sapling clumps during the early stages of gap-phase regeneration. D. pittieri larger than 10 cm dbh are overdispersed at a scale larger than that of patches of gaps. Natural disturbance can influence the distribution of shade intolerant tree populations at several different spatial scales, and can have discordant effects at different life history stages.
NASA Technical Reports Server (NTRS)
Sadowski, F. E.; Sarno, J. E.
1976-01-01
First, an analysis of forest feature signatures was used to help explain the large variation in classification accuracy that can occur among individual forest features for any one case of spatial resolution and the inconsistent changes in classification accuracy that were demonstrated among features as spatial resolution was degraded. Second, the classification rejection threshold was varied in an effort to reduce the large proportion of unclassified resolution elements that previously appeared in the processing of coarse resolution data when a constant rejection threshold was used for all cases of spatial resolution. For the signature analysis, two-channel ellipse plots showing the feature signature distributions for several cases of spatial resolution indicated that the capability of signatures to correctly identify their respective features is dependent on the amount of statistical overlap among signatures. Reductions in signature variance that occur in data of degraded spatial resolution may not necessarily decrease the amount of statistical overlap among signatures having large variance and small mean separations. Features classified by such signatures may thus continue to have similar amounts of misclassified elements in coarser resolution data, and thus, not necessarily improve in classification accuracy.
2014-01-01
Background There have been large-scale outbreaks of hand, foot and mouth disease (HFMD) in Mainland China over the last decade. These events varied greatly across the country. It is necessary to identify the spatial risk factors and spatial distribution patterns of HFMD for public health control and prevention. Climate risk factors associated with HFMD occurrence have been recognized. However, few studies discussed the socio-economic determinants of HFMD risk at a space scale. Methods HFMD records in Mainland China in May 2008 were collected. Both climate and socio-economic factors were selected as potential risk exposures of HFMD. Odds ratio (OR) was used to identify the spatial risk factors. A spatial autologistic regression model was employed to get OR values of each exposures and model the spatial distribution patterns of HFMD risk. Results Results showed that both climate and socio-economic variables were spatial risk factors for HFMD transmission in Mainland China. The statistically significant risk factors are monthly average precipitation (OR = 1.4354), monthly average temperature (OR = 1.379), monthly average wind speed (OR = 1.186), the number of industrial enterprises above designated size (OR = 17.699), the population density (OR = 1.953), and the proportion of student population (OR = 1.286). The spatial autologistic regression model has a good goodness of fit (ROC = 0.817) and prediction accuracy (Correct ratio = 78.45%) of HFMD occurrence. The autologistic regression model also reduces the contribution of the residual term in the ordinary logistic regression model significantly, from 17.25 to 1.25 for the odds ratio. Based on the prediction results of the spatial model, we obtained a map of the probability of HFMD occurrence that shows the spatial distribution pattern and local epidemic risk over Mainland China. Conclusions The autologistic regression model was used to identify spatial risk factors and model spatial risk patterns of HFMD. HFMD occurrences were found to be spatially heterogeneous over the Mainland China, which is related to both the climate and socio-economic variables. The combination of socio-economic and climate exposures can explain the HFMD occurrences more comprehensively and objectively than those with only climate exposures. The modeled probability of HFMD occurrence at the county level reveals not only the spatial trends, but also the local details of epidemic risk, even in the regions where there were no HFMD case records. PMID:24731248
Wildhaber, Mark L.; Lamberson, Peter J.
2004-01-01
Various mechanisms of habitat choice in fishes based on food and/or temperature have been proposed: optimal foraging for food alone; behavioral thermoregulation for temperature alone; and behavioral energetics and discounted matching for food and temperature combined. Along with development of habitat choice mechanisms, there has been a major push to develop and apply to fish populations individual-based models that incorporate various forms of these mechanisms. However, it is not known how the wide variation in observed and hypothesized mechanisms of fish habitat choice could alter fish population predictions (e.g. growth, size distributions, etc.). We used spatially explicit, individual-based modeling to compare predicted fish populations using different submodels of patch choice behavior under various food and temperature distributions. We compared predicted growth, temperature experience, food consumption, and final spatial distribution using the different models. Our results demonstrated that the habitat choice mechanism assumed in fish population modeling simulations was critical to predictions of fish distribution and growth rates. Hence, resource managers who use modeling results to predict fish population trends should be very aware of and understand the underlying patch choice mechanisms used in their models to assure that those mechanisms correctly represent the fish populations being modeled.
NASA Astrophysics Data System (ADS)
Moharana, S.; Dutta, S.
2016-12-01
Abstract : The mapping and analysis of spatial variability within the field is a challenging task. However, field variability of a single vegetation cover does not give satisfactory results mainly due to low spectral resolution and non-availability of remote sensing data. From the NASA Earth Observing-1 (EO-1) satellite data, spatial distribution of biophysical parameters like chlorophyll and relative water content in a rice agriculture system is carried out in the present study. Hyperion L1R product composed of 242 spectral bands with 30m spatial resolution was acquired for Assam, India. This high dimensional data is allowed for pre-processing to get an atmospherically corrected imagery. Moreover, ground based hyperspectral measurements are collected from experimental rice fields from the study site using hand held ASD spectroradiometer (350-1050 nm). Published indices specifically designed for chlorophyll (OASVI, mSR, and MTCI indices) and water content (WI and WBI indices) are selected based on stastical performance of the in-situ hyperspectral data. Index models are established for the respective biophysical parameters and observed that the aforementioned indices followed different linear and nonlinear relationships which are completely different from the published indices. By employing the presently developed relationships, spatial variation of total chlorophyll and water stress are mapped for a rice agriculture system from Hyperion imagery. The findings showed that, the variation of chlorophyll and water content ranged from 1.77-10.61mg/g and 40-90% respectively for the studied rice agriculture system. The spatial distribution of these parameters resulted from presently developed index models are well captured from Hyperion imagery and they have good agreement with observed field based chlorophyll (1.14-7.26 mg/g) and water content (60-95%) of paddy crop. This study can be useful in providing essential information to assess the paddy field heterogeneity in an agriculture system. Keywords: Paddy crop, vegetation index, hyperspectral data, chlorophyll, water content
Galvan, T L; Burkness, E C; Hutchison, W D
2007-06-01
To develop a practical integrated pest management (IPM) system for the multicolored Asian lady beetle, Harmonia axyridis (Pallas) (Coleoptera: Coccinellidae), in wine grapes, we assessed the spatial distribution of H. axyridis and developed eight sampling plans to estimate adult density or infestation level in grape clusters. We used 49 data sets collected from commercial vineyards in 2004 and 2005, in Minnesota and Wisconsin. Enumerative plans were developed using two precision levels (0.10 and 0.25); the six binomial plans reflected six unique action thresholds (3, 7, 12, 18, 22, and 31% of cluster samples infested with at least one H. axyridis). The spatial distribution of H. axyridis in wine grapes was aggregated, independent of cultivar and year, but it was more randomly distributed as mean density declined. The average sample number (ASN) for each sampling plan was determined using resampling software. For research purposes, an enumerative plan with a precision level of 0.10 (SE/X) resulted in a mean ASN of 546 clusters. For IPM applications, the enumerative plan with a precision level of 0.25 resulted in a mean ASN of 180 clusters. In contrast, the binomial plans resulted in much lower ASNs and provided high probabilities of arriving at correct "treat or no-treat" decisions, making these plans more efficient for IPM applications. For a tally threshold of one adult per cluster, the operating characteristic curves for the six action thresholds provided binomial sequential sampling plans with mean ASNs of only 19-26 clusters, and probabilities of making correct decisions between 83 and 96%. The benefits of the binomial sampling plans are discussed within the context of improving IPM programs for wine grapes.
Validation of satellite-based rainfall in Kalahari
NASA Astrophysics Data System (ADS)
Lekula, Moiteela; Lubczynski, Maciek W.; Shemang, Elisha M.; Verhoef, Wouter
2018-06-01
Water resources management in arid and semi-arid areas is hampered by insufficient rainfall data, typically obtained from sparsely distributed rain gauges. Satellite-based rainfall estimates (SREs) are alternative sources of such data in these areas. In this study, daily rainfall estimates from FEWS-RFE∼11 km, TRMM-3B42∼27 km, CMOPRH∼27 km and CMORPH∼8 km were evaluated against nine, daily rain gauge records in Central Kalahari Basin (CKB), over a five-year period, 01/01/2001-31/12/2005. The aims were to evaluate the daily rainfall detection capabilities of the four SRE algorithms, analyze the spatio-temporal variability of rainfall in the CKB and perform bias-correction of the four SREs. Evaluation methods included scatter plot analysis, descriptive statistics, categorical statistics and bias decomposition. The spatio-temporal variability of rainfall, was assessed using the SREs' mean annual rainfall, standard deviation, coefficient of variation and spatial correlation functions. Bias correction of the four SREs was conducted using a Time-Varying Space-Fixed bias-correction scheme. The results underlined the importance of validating daily SREs, as they had different rainfall detection capabilities in the CKB. The FEWS-RFE∼11 km performed best, providing better results of descriptive and categorical statistics than the other three SREs, although bias decomposition showed that all SREs underestimated rainfall. The analysis showed that the most reliable SREs performance analysis indicator were the frequency of "miss" rainfall events and the "miss-bias", as they directly indicated SREs' sensitivity and bias of rainfall detection, respectively. The Time Varying and Space Fixed (TVSF) bias-correction scheme, improved some error measures but resulted in the reduction of the spatial correlation distance, thus increased, already high, spatial rainfall variability of all the four SREs. This study highlighted SREs as valuable source of daily rainfall data providing good spatio-temporal data coverage especially suitable for areas with limited rain gauges, such as the CKB, but also emphasized SREs' drawbacks, creating avenue for follow up research.
Putnam, Christopher M; Bland, Pauline J
2014-01-01
Previous studies of macular pigment optical density (MPOD) distribution in individuals with oculocutaneous albinism (OCA) have primarily used objective measurement techniques including fundus reflectometry and autofluorescence. We report here on a subject with OCA and their corresponding MPOD distribution assessed through heterochromatic flicker photometry (HFP). A subject with a history of OCA presented with an ocular history including strabismus surgery of the LE with persistent amblyopia and mild, latent nystagmus. Best corrected visual acuity was 20/25- RE and 20/40- LE. Spectral domain optical coherence tomography (SD-OCT) and fundus photography were also obtained. Evaluation of MPOD spatial distribution up to 8 degrees eccentricity from the fovea was performed using HFP. SD-OCT indicated a persistence of multiple inner retinal layers within the foveal region in the RE and LE including symmetric foveal thickening consistent with foveal hypoplasia. Fundus photography showed mild retinal pigmented epithelial (RPE) hypopigmentation and a poorly demarcated macula. OriginPro 9 was used to plot MPOD spatial distribution of the subject and a 33-subject sample. The OCA subject demonstrated a foveal MPOD of 0.10 with undetectable levels at 6 degrees eccentricity. The study sample showed a mean foveal MPOD of 0.34 and mean 6 degree eccentricity values of 0.03. Consistent with previous macular pigment (MP) studies of OCA, overall MPOD is reduced in our subject. Mild phenotypic expression of OCA with high functional visual acuity may represent a Henle fiber layer amenable to additional MP deposition. Further study of MP supplementation in OCA patients is warranted. Copyright © 2014 Spanish General Council of Optometry. Published by Elsevier Espana. All rights reserved.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Moriarty, Tom
The NREL cell measurement lab measures the IV parameters of cells of multiple sizes and configurations. A large contributing factor to errors and uncertainty in Jsc, Imax, Pmax and efficiency can be the irradiance spatial nonuniformity. Correcting for this nonuniformity through its precise and frequent measurement can be very time consuming. This paper explains a simple, fast and effective method based on bicubic interpolation for determining and correcting for spatial nonuniformity and verification of the method's efficacy.
Calibration of a distributed hydrologic model using observed spatial patterns from MODIS data
NASA Astrophysics Data System (ADS)
Demirel, Mehmet C.; González, Gorka M.; Mai, Juliane; Stisen, Simon
2016-04-01
Distributed hydrologic models are typically calibrated against streamflow observations at the outlet of the basin. Along with these observations from gauging stations, satellite based estimates offer independent evaluation data such as remotely sensed actual evapotranspiration (aET) and land surface temperature. The primary objective of the study is to compare model calibrations against traditional downstream discharge measurements with calibrations against simulated spatial patterns and combinations of both types of observations. While the discharge based model calibration typically improves the temporal dynamics of the model, it seems to give rise to minimum improvement of the simulated spatial patterns. In contrast, objective functions specifically targeting the spatial pattern performance could potentially increase the spatial model performance. However, most modeling studies, including the model formulations and parameterization, are not designed to actually change the simulated spatial pattern during calibration. This study investigates the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale hydrologic model (mHM). This model is selected as it allows for a change in the spatial distribution of key soil parameters through the optimization of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) values directly as input. In addition the simulated aET can be estimated at a spatial resolution suitable for comparison to the spatial patterns observed with MODIS data. To increase our control on spatial calibration we introduced three additional parameters to the model. These new parameters are part of an empirical equation to the calculate crop coefficient (Kc) from daily LAI maps and used to update potential evapotranspiration (PET) as model inputs. This is done instead of correcting/updating PET with just a uniform (or aspect driven) factor used in the mHM model (version 5.3). We selected the 20 most important parameters out of 53 mHM parameters based on a comprehensive sensitivity analysis (Cuntz et al., 2015). We calibrated 1km-daily mHM for the Skjern basin in Denmark using the Shuffled Complex Evolution (SCE) algorithm and inputs at different spatial scales i.e. meteorological data at 10km and morphological data at 250 meters. We used correlation coefficients between observed monthly (summer months only) MODIS data calculated from cloud free days over the calibration period from 2001 to 2008 and simulated aET from mHM over the same period. Similarly other metrics, e.g mapcurves and fraction skill-score, are also included in our objective function to assess the co-location of the grid-cells. The preliminary results show that multi-objective calibration of mHM against observed streamflow and spatial patterns together does not significantly reduce the spatial errors in aET while it improves the streamflow simulations. This is a strong signal for further investigation of the multi parameter regionalization affecting spatial aET patterns and weighting the spatial metrics in the objective function relative to the streamflow metrics.
Search for new physics with dijet angular distributions in proton-proton collisions at √{s}=13 TeV
NASA Astrophysics Data System (ADS)
Sirunyan, A. M.; Tumasyan, A.; Adam, W.; Asilar, E.; Bergauer, T.; Brandstetter, J.; Brondolin, E.; Dragicevic, M.; Erö, J.; Flechl, M.; Friedl, M.; Frühwirth, R.; Ghete, V. M.; Hartl, C.; Hörmann, N.; Hrubec, J.; Jeitler, M.; König, A.; Krätschmer, I.; Liko, D.; Matsushita, T.; Mikulec, I.; Rabady, D.; Rad, N.; Rahbaran, B.; Rohringer, H.; Schieck, J.; Strauss, J.; Waltenberger, W.; Wulz, C.-E.; Dvornikov, O.; Makarenko, V.; Mossolov, V.; Suarez Gonzalez, J.; Zykunov, V.; Shumeiko, N.; Alderweireldt, S.; De Wolf, E. A.; Janssen, X.; Lauwers, J.; Van De Klundert, M.; Van Haevermaet, H.; Van Mechelen, P.; Van Remortel, N.; Van Spilbeeck, A.; Abu Zeid, S.; Blekman, F.; D'Hondt, J.; Daci, N.; De Bruyn, I.; Deroover, K.; Lowette, S.; Moortgat, S.; Moreels, L.; Olbrechts, A.; Python, Q.; Skovpen, K.; Tavernier, S.; Van Doninck, W.; Van Mulders, P.; Van Parijs, I.; Brun, H.; Clerbaux, B.; De Lentdecker, G.; Delannoy, H.; Fasanella, G.; Favart, L.; Goldouzian, R.; Grebenyuk, A.; Karapostoli, G.; Lenzi, T.; Léonard, A.; Luetic, J.; Maerschalk, T.; Marinov, A.; Randle-conde, A.; Seva, T.; Vander Velde, C.; Vanlaer, P.; Vannerom, D.; Yonamine, R.; Zenoni, F.; Zhang, F.; Cimmino, A.; Cornelis, T.; Dobur, D.; Fagot, A.; Gul, M.; Khvastunov, I.; Poyraz, D.; Salva, S.; Schöfbeck, R.; Tytgat, M.; Van Driessche, W.; Yazgan, E.; Zaganidis, N.; Bakhshiansohi, H.; Beluffi, C.; Bondu, O.; Brochet, S.; Bruno, G.; Caudron, A.; De Visscher, S.; Delaere, C.; Delcourt, M.; Francois, B.; Giammanco, A.; Jafari, A.; Komm, M.; Krintiras, G.; Lemaitre, V.; Magitteri, A.; Mertens, A.; Musich, M.; Piotrzkowski, K.; Quertenmont, L.; Selvaggi, M.; Vidal Marono, M.; Wertz, S.; Beliy, N.; Aldá Júnior, W. L.; Alves, F. L.; Alves, G. A.; Brito, L.; Hensel, C.; Moraes, A.; Pol, M. E.; Rebello Teles, P.; Belchior Batista Das Chagas, E.; Carvalho, W.; Chinellato, J.; Custódio, A.; Da Costa, E. M.; Da Silveira, G. G.; De Jesus Damiao, D.; De Oliveira Martins, C.; Fonseca De Souza, S.; Huertas Guativa, L. M.; Malbouisson, H.; Matos Figueiredo, D.; Mora Herrera, C.; Mundim, L.; Nogima, H.; Prado Da Silva, W. L.; Santoro, A.; Sznajder, A.; Tonelli Manganote, E. J.; Torres Da Silva De Araujo, F.; Vilela Pereira, A.; Ahuja, S.; Bernardes, C. A.; Dogra, S.; Fernandez Perez Tomei, T. R.; Gregores, E. M.; Mercadante, P. G.; Moon, C. S.; Novaes, S. F.; Padula, Sandra S.; Romero Abad, D.; Ruiz Vargas, J. C.; Aleksandrov, A.; Hadjiiska, R.; Iaydjiev, P.; Rodozov, M.; Stoykova, S.; Sultanov, G.; Vutova, M.; Dimitrov, A.; Glushkov, I.; Litov, L.; Pavlov, B.; Petkov, P.; Fang, W.; Ahmad, M.; Bian, J. G.; Chen, G. M.; Chen, H. S.; Chen, M.; Chen, Y.; Cheng, T.; Jiang, C. H.; Leggat, D.; Liu, Z.; Romeo, F.; Ruan, M.; Shaheen, S. M.; Spiezia, A.; Tao, J.; Wang, C.; Wang, Z.; Zhang, H.; Zhao, J.; Ban, Y.; Chen, G.; Li, Q.; Liu, S.; Mao, Y.; Qian, S. J.; Wang, D.; Xu, Z.; Avila, C.; Cabrera, A.; Chaparro Sierra, L. F.; Florez, C.; Gomez, J. P.; González Hernández, C. F.; Ruiz Alvarez, J. D.; Sanabria, J. C.; Godinovic, N.; Lelas, D.; Puljak, I.; Ribeiro Cipriano, P. M.; Sculac, T.; Antunovic, Z.; Kovac, M.; Brigljevic, V.; Ferencek, D.; Kadija, K.; Mesic, B.; Susa, T.; Attikis, A.; Mavromanolakis, G.; Mousa, J.; Nicolaou, C.; Ptochos, F.; Razis, P. A.; Rykaczewski, H.; Tsiakkouri, D.; Finger, M.; Finger, M.; Carrera Jarrin, E.; Abdelalim, A. A.; Mohammed, Y.; Salama, E.; Kadastik, M.; Perrini, L.; Raidal, M.; Tiko, A.; Veelken, C.; Eerola, P.; Pekkanen, J.; Voutilainen, M.; Härkönen, J.; Järvinen, T.; Karimäki, V.; Kinnunen, R.; Lampén, T.; Lassila-Perini, K.; Lehti, S.; Lindén, T.; Luukka, P.; Tuominiemi, J.; Tuovinen, E.; Wendland, L.; Talvitie, J.; Tuuva, T.; Besancon, M.; Couderc, F.; Dejardin, M.; Denegri, D.; Fabbro, B.; Faure, J. L.; Favaro, C.; Ferri, F.; Ganjour, S.; Ghosh, S.; Givernaud, A.; Gras, P.; Hamel de Monchenault, G.; Jarry, P.; Kucher, I.; Locci, E.; Machet, M.; Malcles, J.; Rander, J.; Rosowsky, A.; Titov, M.; Abdulsalam, A.; Antropov, I.; Baffioni, S.; Beaudette, F.; Busson, P.; Cadamuro, L.; Chapon, E.; Charlot, C.; Davignon, O.; Granier de Cassagnac, R.; Jo, M.; Lisniak, S.; Miné, P.; Nguyen, M.; Ochando, C.; Ortona, G.; Paganini, P.; Pigard, P.; Regnard, S.; Salerno, R.; Sirois, Y.; Strebler, T.; Yilmaz, Y.; Zabi, A.; Zghiche, A.; Agram, J.-L.; Andrea, J.; Aubin, A.; Bloch, D.; Brom, J.-M.; Buttignol, M.; Chabert, E. C.; Chanon, N.; Collard, C.; Conte, E.; Coubez, X.; Fontaine, J.-C.; Gelé, D.; Goerlach, U.; Le Bihan, A.-C.; Van Hove, P.; Gadrat, S.; Beauceron, S.; Bernet, C.; Boudoul, G.; Carrillo Montoya, C. A.; Chierici, R.; Contardo, D.; Courbon, B.; Depasse, P.; El Mamouni, H.; Fay, J.; Gascon, S.; Gouzevitch, M.; Grenier, G.; Ille, B.; Lagarde, F.; Laktineh, I. B.; Lethuillier, M.; Mirabito, L.; Pequegnot, A. L.; Perries, S.; Popov, A.; Sabes, D.; Sordini, V.; Vander Donckt, M.; Verdier, P.; Viret, S.; Toriashvili, T.; Tsamalaidze, Z.; Autermann, C.; Beranek, S.; Feld, L.; Kiesel, M. K.; Klein, K.; Lipinski, M.; Preuten, M.; Schomakers, C.; Schulz, J.; Verlage, T.; Albert, A.; Brodski, M.; Dietz-Laursonn, E.; Duchardt, D.; Endres, M.; Erdmann, M.; Erdweg, S.; Esch, T.; Fischer, R.; Güth, A.; Hamer, M.; Hebbeker, T.; Heidemann, C.; Hoepfner, K.; Knutzen, S.; Merschmeyer, M.; Meyer, A.; Millet, P.; Mukherjee, S.; Olschewski, M.; Padeken, K.; Pook, T.; Radziej, M.; Reithler, H.; Rieger, M.; Scheuch, F.; Sonnenschein, L.; Teyssier, D.; Thüer, S.; Cherepanov, V.; Flügge, G.; Kargoll, B.; Kress, T.; Künsken, A.; Lingemann, J.; Müller, T.; Nehrkorn, A.; Nowack, A.; Pistone, C.; Pooth, O.; Stahl, A.; Aldaya Martin, M.; Arndt, T.; Asawatangtrakuldee, C.; Beernaert, K.; Behnke, O.; Behrens, U.; Bin Anuar, A. A.; Borras, K.; Campbell, A.; Connor, P.; Contreras-Campana, C.; Costanza, F.; Diez Pardos, C.; Dolinska, G.; Eckerlin, G.; Eckstein, D.; Eichhorn, T.; Eren, E.; Gallo, E.; Garay Garcia, J.; Geiser, A.; Gizhko, A.; Grados Luyando, J. M.; Grohsjean, A.; Gunnellini, P.; Harb, A.; Hauk, J.; Hempel, M.; Jung, H.; Kalogeropoulos, A.; Karacheban, O.; Kasemann, M.; Keaveney, J.; Kleinwort, C.; Korol, I.; Krücker, D.; Lange, W.; Lelek, A.; Lenz, T.; Leonard, J.; Lipka, K.; Lobanov, A.; Lohmann, W.; Mankel, R.; Melzer-Pellmann, I.-A.; Meyer, A. B.; Mittag, G.; Mnich, J.; Mussgiller, A.; Pitzl, D.; Placakyte, R.; Raspereza, A.; Roland, B.; Sahin, M. Ö.; Saxena, P.; SchoernerSadenius, T.; Spannagel, S.; Stefaniuk, N.; Van Onsem, G. P.; Walsh, R.; Wissing, C.; Blobel, V.; Centis Vignali, M.; Draeger, A. R.; Dreyer, T.; Garutti, E.; Gonzalez, D.; Haller, J.; Hoffmann, M.; Junkes, A.; Klanner, R.; Kogler, R.; Kovalchuk, N.; Lapsien, T.; Marchesini, I.; Marconi, D.; Meyer, M.; Niedziela, M.; Nowatschin, D.; Pantaleo, F.; Peiffer, T.; Perieanu, A.; Poehlsen, J.; Scharf, C.; Schleper, P.; Schmidt, A.; Schumann, S.; Schwandt, J.; Stadie, H.; Steinbrück, G.; Stober, F. M.; Stöver, M.; Tholen, H.; Troendle, D.; Usai, E.; Vanelderen, L.; Vanhoefer, A.; Vormwald, B.; Akbiyik, M.; Barth, C.; Baur, S.; Baus, C.; Berger, J.; Butz, E.; Caspart, R.; Chwalek, T.; Colombo, F.; De Boer, W.; Dierlamm, A.; Fink, S.; Freund, B.; Friese, R.; Giffels, M.; Gilbert, A.; Goldenzweig, P.; Haitz, D.; Hartmann, F.; Heindl, S. M.; Husemann, U.; Katkov, I.; Kudella, S.; Mildner, H.; Mozer, M. U.; Müller, Th.; Plagge, M.; Quast, G.; Rabbertz, K.; Röcker, S.; Roscher, F.; Schröder, M.; Shvetsov, I.; Sieber, G.; Simonis, H. J.; Ulrich, R.; Wayand, S.; Weber, M.; Weiler, T.; Williamson, S.; Wöhrmann, C.; Wolf, R.; Anagnostou, G.; Daskalakis, G.; Geralis, T.; Giakoumopoulou, V. A.; Kyriakis, A.; Loukas, D.; Topsis-Giotis, I.; Kesisoglou, S.; Panagiotou, A.; Saoulidou, N.; Tziaferi, E.; Evangelou, I.; Flouris, G.; Foudas, C.; Kokkas, P.; Loukas, N.; Manthos, N.; Papadopoulos, I.; Paradas, E.; Filipovic, N.; Pasztor, G.; Bencze, G.; Hajdu, C.; Horvath, D.; Sikler, F.; Veszpremi, V.; Vesztergombi, G.; Zsigmond, A. J.; Beni, N.; Czellar, S.; Karancsi, J.; Makovec, A.; Molnar, J.; Szillasi, Z.; Bartók, M.; Raics, P.; Trocsanyi, Z. L.; Ujvari, B.; Komaragiri, J. R.; Bahinipati, S.; Bhowmik, S.; Choudhury, S.; Mal, P.; Mandal, K.; Nayak, A.; Sahoo, D. K.; Sahoo, N.; Swain, S. K.; Bansal, S.; Beri, S. B.; Bhatnagar, V.; Chawla, R.; Bhawandeep, U.; Kalsi, A. K.; Kaur, A.; Kaur, M.; Kumar, R.; Kumari, P.; Mehta, A.; Mittal, M.; Singh, J. B.; Walia, G.; Kumar, Ashok; Bhardwaj, A.; Choudhary, B. C.; Garg, R. B.; Keshri, S.; Malhotra, S.; Naimuddin, M.; Ranjan, K.; Sharma, R.; Sharma, V.; Bhattacharya, R.; Bhattacharya, S.; Chatterjee, K.; Dey, S.; Dutt, S.; Dutta, S.; Ghosh, S.; Majumdar, N.; Modak, A.; Mondal, K.; Mukhopadhyay, S.; Nandan, S.; Purohit, A.; Roy, A.; Roy, D.; Roy Chowdhury, S.; Sarkar, S.; Sharan, M.; Thakur, S.; Behera, P. K.; Chudasama, R.; Dutta, D.; Jha, V.; Kumar, V.; Mohanty, A. K.; Netrakanti, P. K.; Pant, L. M.; Shukla, P.; Topkar, A.; Aziz, T.; Dugad, S.; Kole, G.; Mahakud, B.; Mitra, S.; Mohanty, G. B.; Parida, B.; Sur, N.; Sutar, B.; Banerjee, S.; Dewanjee, R. K.; Ganguly, S.; Guchait, M.; Jain, Sa.; Kumar, S.; Maity, M.; Majumder, G.; Mazumdar, K.; Sarkar, T.; Wickramage, N.; Chauhan, S.; Dube, S.; Hegde, V.; Kapoor, A.; Kothekar, K.; Pandey, S.; Rane, A.; Sharma, S.; Chenarani, S.; Eskandari Tadavani, E.; Etesami, S. M.; Khakzad, M.; Mohammadi Najafabadi, M.; Naseri, M.; Paktinat Mehdiabadi, S.; Rezaei Hosseinabadi, F.; Safarzadeh, B.; Zeinali, M.; Felcini, M.; Grunewald, M.; Abbrescia, M.; Calabria, C.; Caputo, C.; Colaleo, A.; Creanza, D.; Cristella, L.; De Filippis, N.; De Palma, M.; Fiore, L.; Iaselli, G.; Maggi, G.; Maggi, M.; Miniello, G.; My, S.; Nuzzo, S.; Pompili, A.; Pugliese, G.; Radogna, R.; Ranieri, A.; Selvaggi, G.; Sharma, A.; Silvestris, L.; Venditti, R.; Verwilligen, P.; Abbiendi, G.; Battilana, C.; Bonacorsi, D.; Braibant-Giacomelli, S.; Brigliadori, L.; Campanini, R.; Capiluppi, P.; Castro, A.; Cavallo, F. R.; Chhibra, S. S.; Codispoti, G.; Cuffiani, M.; Dallavalle, G. M.; Fabbri, F.; Fanfani, A.; Fasanella, D.; Giacomelli, P.; Grandi, C.; Guiducci, L.; Marcellini, S.; Masetti, G.; Montanari, A.; Navarria, F. L.; Perrotta, A.; Rossi, A. M.; Rovelli, T.; Siroli, G. P.; Tosi, N.; Albergo, S.; Costa, S.; Di Mattia, A.; Giordano, F.; Potenza, R.; Tricomi, A.; Tuve, C.; Barbagli, G.; Ciulli, V.; Civinini, C.; D'Alessandro, R.; Focardi, E.; Lenzi, P.; Meschini, M.; Paoletti, S.; Russo, L.; Sguazzoni, G.; Strom, D.; Viliani, L.; Benussi, L.; Bianco, S.; Fabbri, F.; Piccolo, D.; Primavera, F.; Calvelli, V.; Ferro, F.; Monge, M. R.; Robutti, E.; Tosi, S.; Brianza, L.; Brivio, F.; Ciriolo, V.; Dinardo, M. E.; Fiorendi, S.; Gennai, S.; Ghezzi, A.; Govoni, P.; Malberti, M.; Malvezzi, S.; Manzoni, R. A.; Menasce, D.; Moroni, L.; Paganoni, M.; Pedrini, D.; Pigazzini, S.; Ragazzi, S.; Tabarelli de Fatis, T.; Buontempo, S.; Cavallo, N.; De Nardo, G.; Di Guida, S.; Esposito, M.; Fabozzi, F.; Fienga, F.; Iorio, A. O. M.; Lanza, G.; Lista, L.; Meola, S.; Paolucci, P.; Sciacca, C.; Thyssen, F.; Azzi, P.; Bacchetta, N.; Benato, L.; Bisello, D.; Boletti, A.; Carlin, R.; Carvalho Antunes De Oliveira, A.; Checchia, P.; Dall'Osso, M.; De Castro Manzano, P.; Dorigo, T.; Dosselli, U.; Gasparini, F.; Gasparini, U.; Gozzelino, A.; Lacaprara, S.; Margoni, M.; Meneguzzo, A. T.; Pazzini, J.; Pozzobon, N.; Ronchese, P.; Simonetto, F.; Torassa, E.; Zanetti, M.; Zotto, P.; Zumerle, G.; Braghieri, A.; Fallavollita, F.; Magnani, A.; Montagna, P.; Ratti, S. P.; Re, V.; Riccardi, C.; Salvini, P.; Vai, I.; Vitulo, P.; Alunni Solestizi, L.; Bilei, G. M.; Ciangottini, D.; Fanò, L.; Lariccia, P.; Leonardi, R.; Mantovani, G.; Menichelli, M.; Saha, A.; Santocchia, A.; Androsov, K.; Azzurri, P.; Bagliesi, G.; Bernardini, J.; Boccali, T.; Castaldi, R.; Ciocci, M. A.; Dell'Orso, R.; Donato, S.; Fedi, G.; Giassi, A.; Grippo, M. T.; Ligabue, F.; Lomtadze, T.; Martini, L.; Messineo, A.; Palla, F.; Rizzi, A.; Savoy-Navarro, A.; Spagnolo, P.; Tenchini, R.; Tonelli, G.; Venturi, A.; Verdini, P. G.; Barone, L.; Cavallari, F.; Cipriani, M.; Del Re, D.; Diemoz, M.; Gelli, S.; Longo, E.; Margaroli, F.; Marzocchi, B.; Meridiani, P.; Organtini, G.; Paramatti, R.; Preiato, F.; Rahatlou, S.; Rovelli, C.; Santanastasio, F.; Amapane, N.; Arcidiacono, R.; Argiro, S.; Arneodo, M.; Bartosik, N.; Bellan, R.; Biino, C.; Cartiglia, N.; Cenna, F.; Costa, M.; Covarelli, R.; Degano, A.; Demaria, N.; Finco, L.; Kiani, B.; Mariotti, C.; Maselli, S.; Migliore, E.; Monaco, V.; Monteil, E.; Monteno, M.; Obertino, M. M.; Pacher, L.; Pastrone, N.; Pelliccioni, M.; Pinna Angioni, G. L.; Ravera, F.; Romero, A.; Ruspa, M.; Sacchi, R.; Shchelina, K.; Sola, V.; Solano, A.; Staiano, A.; Traczyk, P.; Belforte, S.; Casarsa, M.; Cossutti, F.; Della Ricca, G.; Zanetti, A.; Kim, D. H.; Kim, G. N.; Kim, M. S.; Lee, S.; Lee, S. W.; Oh, Y. D.; Sekmen, S.; Son, D. C.; Yang, Y. C.; Lee, A.; Kim, H.; Brochero Cifuentes, J. A.; Kim, T. J.; Cho, S.; Choi, S.; Go, Y.; Gyun, D.; Ha, S.; Hong, B.; Jo, Y.; Kim, Y.; Lee, K.; Lee, K. S.; Lee, S.; Lim, J.; Park, S. K.; Roh, Y.; Almond, J.; Kim, J.; Lee, H.; Oh, S. B.; Radburn-Smith, B. C.; Seo, S. h.; Yang, U. K.; Yoo, H. D.; Yu, G. B.; Choi, M.; Kim, H.; Kim, J. H.; Lee, J. S. H.; Park, I. C.; Ryu, G.; Ryu, M. S.; Choi, Y.; Goh, J.; Hwang, C.; Lee, J.; Yu, I.; Dudenas, V.; Juodagalvis, A.; Vaitkus, J.; Ahmed, I.; Ibrahim, Z. A.; Ali, M. A. B. Md; Mohamad Idris, F.; Wan Abdullah, W. A. T.; Yusli, M. N.; Zolkapli, Z.; Castilla-Valdez, H.; De La Cruz-Burelo, E.; Heredia-De La Cruz, I.; Hernandez-Almada, A.; Lopez-Fernandez, R.; Magaña Villalba, R.; Mejia Guisao, J.; Sanchez-Hernandez, A.; Carrillo Moreno, S.; Oropeza Barrera, C.; Vazquez Valencia, F.; Carpinteyro, S.; Pedraza, I.; Salazar Ibarguen, H. A.; Uribe Estrada, C.; Morelos Pineda, A.; Krofcheck, D.; Butler, P. H.; Ahmad, A.; Ahmad, M.; Hassan, Q.; Hoorani, H. R.; Khan, W. A.; Saddique, A.; Shah, M. A.; Shoaib, M.; Waqas, M.; Bialkowska, H.; Bluj, M.; Boimska, B.; Frueboes, T.; Górski, M.; Kazana, M.; Nawrocki, K.; Romanowska-Rybinska, K.; Szleper, M.; Zalewski, P.; Bunkowski, K.; Byszuk, A.; Doroba, K.; Kalinowski, A.; Konecki, M.; Krolikowski, J.; Misiura, M.; Olszewski, M.; Walczak, M.; Bargassa, P.; Beirão Da Cruz E Silva, C.; Calpas, B.; Di Francesco, A.; Faccioli, P.; Ferreira Parracho, P. G.; Gallinaro, M.; Hollar, J.; Leonardo, N.; Lloret Iglesias, L.; Nemallapudi, M. V.; Rodrigues Antunes, J.; Seixas, J.; Toldaiev, O.; Vadruccio, D.; Varela, J.; Vischia, P.; Afanasiev, S.; Alexakhin, V.; Bunin, P.; Gavrilenko, M.; Golutvin, I.; Kamenev, A.; Karjavin, V.; Lanev, A.; Malakhov, A.; Matveev, V.; Palichik, V.; Perelygin, V.; Savina, M.; Shmatov, S.; Shulha, S.; Skatchkov, N.; Smirnov, V.; Zarubin, A.; Chtchipounov, L.; Golovtsov, V.; Ivanov, Y.; Kim, V.; Kuznetsova, E.; Murzin, V.; Oreshkin, V.; Sulimov, V.; Vorobyev, A.; Andreev, Yu.; Dermenev, A.; Gninenko, S.; Golubev, N.; Karneyeu, A.; Kirsanov, M.; Krasnikov, N.; Pashenkov, A.; Tlisov, D.; Toropin, A.; Epshteyn, V.; Gavrilov, V.; Lychkovskaya, N.; Popov, V.; Pozdnyakov, I.; Safronov, G.; Spiridonov, A.; Toms, M.; Vlasov, E.; Zhokin, A.; Bylinkin, A.; Chistov, R.; Polikarpov, S.; Zhemchugov, E.; Andreev, V.; Azarkin, M.; Dremin, I.; Kirakosyan, M.; Leonidov, A.; Terkulov, A.; Baskakov, A.; Belyaev, A.; Boos, E.; Dubinin, M.; Dudko, L.; Ershov, A.; Gribushin, A.; Klyukhin, V.; Kodolova, O.; Lokhtin, I.; Miagkov, I.; Obraztsov, S.; Petrushanko, S.; Savrin, V.; Snigirev, A.; Blinov, V.; Skovpen, Y.; Shtol, D.; Azhgirey, I.; Bayshev, I.; Bitioukov, S.; Elumakhov, D.; Kachanov, V.; Kalinin, A.; Konstantinov, D.; Krychkine, V.; Petrov, V.; Ryutin, R.; Sobol, A.; Troshin, S.; Tyurin, N.; Uzunian, A.; Volkov, A.; Adzic, P.; Cirkovic, P.; Devetak, D.; Dordevic, M.; Milosevic, J.; Rekovic, V.; Alcaraz Maestre, J.; Barrio Luna, M.; Calvo, E.; Cerrada, M.; Chamizo Llatas, M.; Colino, N.; De La Cruz, B.; Delgado Peris, A.; Escalante Del Valle, A.; Fernandez Bedoya, C.; Fernández Ramos, J. P.; Flix, J.; Fouz, M. C.; Garcia-Abia, P.; Gonzalez Lopez, O.; Goy Lopez, S.; Hernandez, J. M.; Josa, M. I.; Navarro De Martino, E.; Pérez-Calero Yzquierdo, A.; Puerta Pelayo, J.; Quintario Olmeda, A.; Redondo, I.; Romero, L.; Soares, M. S.; de Trocóniz, J. F.; Missiroli, M.; Moran, D.; Cuevas, J.; Fernandez Menendez, J.; Gonzalez Caballero, I.; González Fernández, J. R.; Palencia Cortezon, E.; Sanchez Cruz, S.; Suárez Andrés, I.; Vizan Garcia, J. M.; Cabrillo, I. J.; Calderon, A.; Curras, E.; Fernandez, M.; Garcia-Ferrero, J.; Gomez, G.; Lopez Virto, A.; Marco, J.; Martinez Rivero, C.; Matorras, F.; Piedra Gomez, J.; Rodrigo, T.; Ruiz-Jimeno, A.; Scodellaro, L.; Trevisani, N.; Vila, I.; Vilar Cortabitarte, R.; Abbaneo, D.; Auffray, E.; Auzinger, G.; Baillon, P.; Ball, A. H.; Barney, D.; Bloch, P.; Bocci, A.; Botta, C.; Camporesi, T.; Castello, R.; Cepeda, M.; Cerminara, G.; Chen, Y.; d'Enterria, D.; Dabrowski, A.; Daponte, V.; David, A.; De Gruttola, M.; De Roeck, A.; Di Marco, E.; Dobson, M.; Dorney, B.; du Pree, T.; Duggan, D.; Dünser, M.; Dupont, N.; Elliott-Peisert, A.; Everaerts, P.; Fartoukh, S.; Franzoni, G.; Fulcher, J.; Funk, W.; Gigi, D.; Gill, K.; Girone, M.; Glege, F.; Gulhan, D.; Gundacker, S.; Guthoff, M.; Harris, P.; Hegeman, J.; Innocente, V.; Janot, P.; Kieseler, J.; Kirschenmann, H.; Knünz, V.; Kornmayer, A.; Kortelainen, M. J.; Kousouris, K.; Krammer, M.; Lange, C.; Lecoq, P.; Lourenço, C.; Lucchini, M. T.; Malgeri, L.; Mannelli, M.; Martelli, A.; Meijers, F.; Merlin, J. A.; Mersi, S.; Meschi, E.; Milenovic, P.; Moortgat, F.; Morovic, S.; Mulders, M.; Neugebauer, H.; Orfanelli, S.; Orsini, L.; Pape, L.; Perez, E.; Peruzzi, M.; Petrilli, A.; Petrucciani, G.; Pfeiffer, A.; Pierini, M.; Racz, A.; Reis, T.; Rolandi, G.; Rovere, M.; Sakulin, H.; Sauvan, J. B.; Schäfer, C.; Schwick, C.; Seidel, M.; Sharma, A.; Silva, P.; Sphicas, P.; Steggemann, J.; Stoye, M.; Takahashi, Y.; Tosi, M.; Treille, D.; Triossi, A.; Tsirou, A.; Veckalns, V.; Veres, G. I.; Verweij, M.; Wardle, N.; Wöhri, H. K.; Zagozdzinska, A.; Zeuner, W. D.; Bertl, W.; Deiters, K.; Erdmann, W.; Horisberger, R.; Ingram, Q.; Kaestli, H. C.; Kotlinski, D.; Langenegger, U.; Rohe, T.; Bachmair, F.; Bäni, L.; Bianchini, L.; Casal, B.; Dissertori, G.; Dittmar, M.; Donegà, M.; Grab, C.; Heidegger, C.; Hits, D.; Hoss, J.; Kasieczka, G.; Lustermann, W.; Mangano, B.; Marionneau, M.; Martinez Ruiz del Arbol, P.; Masciovecchio, M.; Meinhard, M. T.; Meister, D.; Micheli, F.; Musella, P.; Nessi-Tedaldi, F.; Pandolfi, F.; Pata, J.; Pauss, F.; Perrin, G.; Perrozzi, L.; Quittnat, M.; Rossini, M.; Schönenberger, M.; Starodumov, A.; Tavolaro, V. R.; Theofilatos, K.; Wallny, R.; Aarrestad, T. K.; Amsler, C.; Caminada, L.; Canelli, M. F.; De Cosa, A.; Galloni, C.; Hinzmann, A.; Hreus, T.; Kilminster, B.; Ngadiuba, J.; Pinna, D.; Rauco, G.; Robmann, P.; Salerno, D.; Seitz, C.; Yang, Y.; Zucchetta, A.; Candelise, V.; Doan, T. H.; Jain, Sh.; Khurana, R.; Konyushikhin, M.; Kuo, C. M.; Lin, W.; Pozdnyakov, A.; Yu, S. S.; Kumar, Arun; Chang, P.; Chang, Y. H.; Chao, Y.; Chen, K. F.; Chen, P. H.; Fiori, F.; Hou, W.-S.; Hsiung, Y.; Liu, Y. F.; Lu, R.-S.; Miñano Moya, M.; Paganis, E.; Psallidas, A.; Tsai, J. f.; Asavapibhop, B.; Singh, G.; Srimanobhas, N.; Suwonjandee, N.; Adiguzel, A.; Cerci, S.; Damarseckin, S.; Demiroglu, Z. S.; Dozen, C.; Dumanoglu, I.; Girgis, S.; Gokbulut, G.; Guler, Y.; Hos, I.; Kangal, E. 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R.; Williams, T.; Baber, M.; Bainbridge, R.; Buchmuller, O.; Bundock, A.; Burton, D.; Casasso, S.; Citron, M.; Colling, D.; Corpe, L.; Dauncey, P.; Davies, G.; De Wit, A.; Della Negra, M.; Di Maria, R.; Dunne, P.; Elwood, A.; Futyan, D.; Haddad, Y.; Hall, G.; Iles, G.; James, T.; Lane, R.; Laner, C.; Lucas, R.; Lyons, L.; Magnan, A.-M.; Malik, S.; Mastrolorenzo, L.; Nash, J.; Nikitenko, A.; Pela, J.; Penning, B.; Pesaresi, M.; Raymond, D. M.; Richards, A.; Rose, A.; Scott, E.; Seez, C.; Summers, S.; Tapper, A.; Uchida, K.; Vazquez Acosta, M.; Virdee, T.; Wright, J.; Zenz, S. C.; Cole, J. E.; Hobson, P. R.; Khan, A.; Kyberd, P.; Reid, I. D.; Symonds, P.; Teodorescu, L.; Turner, M.; Borzou, A.; Call, K.; Dittmann, J.; Hatakeyama, K.; Liu, H.; Pastika, N.; Bartek, R.; Dominguez, A.; Buccilli, A.; Cooper, S. I.; Henderson, C.; Rumerio, P.; West, C.; Arcaro, D.; Avetisyan, A.; Bose, T.; Gastler, D.; Rankin, D.; Richardson, C.; Rohlf, J.; Sulak, L.; Zou, D.; Benelli, G.; Cutts, D.; Garabedian, A.; Hakala, J.; Heintz, U.; Hogan, J. M.; Jesus, O.; Kwok, K. H. M.; Laird, E.; Landsberg, G.; Mao, Z.; Narain, M.; Piperov, S.; Sagir, S.; Spencer, E.; Syarif, R.; Breedon, R.; Burns, D.; Calderon De La Barca Sanchez, M.; Chauhan, S.; Chertok, M.; Conway, J.; Conway, R.; Cox, P. T.; Erbacher, R.; Flores, C.; Funk, G.; Gardner, M.; Ko, W.; Lander, R.; Mclean, C.; Mulhearn, M.; Pellett, D.; Pilot, J.; Shalhout, S.; Shi, M.; Smith, J.; Squires, M.; Stolp, D.; Tos, K.; Tripathi, M.; Bachtis, M.; Bravo, C.; Cousins, R.; Dasgupta, A.; Florent, A.; Hauser, J.; Ignatenko, M.; Mccoll, N.; Saltzberg, D.; Schnaible, C.; Valuev, V.; Weber, M.; Bouvier, E.; Burt, K.; Clare, R.; Ellison, J.; Gary, J. W.; Ghiasi Shirazi, S. M. A.; Hanson, G.; Heilman, J.; Jandir, P.; Kennedy, E.; Lacroix, F.; Long, O. R.; Olmedo Negrete, M.; Paneva, M. I.; Shrinivas, A.; Si, W.; Wei, H.; Wimpenny, S.; Yates, B. R.; Branson, J. G.; Cerati, G. B.; Cittolin, S.; Derdzinski, M.; Gerosa, R.; Holzner, A.; Klein, D.; Krutelyov, V.; Letts, J.; Macneill, I.; Olivito, D.; Padhi, S.; Pieri, M.; Sani, M.; Sharma, V.; Simon, S.; Tadel, M.; Vartak, A.; Wasserbaech, S.; Welke, C.; Wood, J.; Würthwein, F.; Yagil, A.; Zevi Della Porta, G.; Amin, N.; Bhandari, R.; Bradmiller-Feld, J.; Campagnari, C.; Dishaw, A.; Dutta, V.; Franco Sevilla, M.; George, C.; Golf, F.; Gouskos, L.; Gran, J.; Heller, R.; Incandela, J.; Mullin, S. D.; Ovcharova, A.; Qu, H.; Richman, J.; Stuart, D.; Suarez, I.; Yoo, J.; Anderson, D.; Bendavid, J.; Bornheim, A.; Bunn, J.; Duarte, J.; Lawhorn, J. M.; Mott, A.; Newman, H. B.; Pena, C.; Spiropulu, M.; Vlimant, J. R.; Xie, S.; Zhu, R. Y.; Andrews, M. B.; Ferguson, T.; Paulini, M.; Russ, J.; Sun, M.; Vogel, H.; Vorobiev, I.; Weinberg, M.; Cumalat, J. P.; Ford, W. T.; Jensen, F.; Johnson, A.; Krohn, M.; Leontsinis, S.; Mulholland, T.; Stenson, K.; Wagner, S. R.; Alexander, J.; Chaves, J.; Chu, J.; Dittmer, S.; Mcdermott, K.; Mirman, N.; Nicolas Kaufman, G.; Patterson, J. R.; Rinkevicius, A.; Ryd, A.; Skinnari, L.; Soffi, L.; Tan, S. M.; Tao, Z.; Thom, J.; Tucker, J.; Wittich, P.; Zientek, M.; Winn, D.; Abdullin, S.; Albrow, M.; Apollinari, G.; Apresyan, A.; Banerjee, S.; Bauerdick, L. A. T.; Beretvas, A.; Berryhill, J.; Bhat, P. C.; Bolla, G.; Burkett, K.; Butler, J. N.; Cheung, H. W. K.; Chlebana, F.; Cihangir, S.; Cremonesi, M.; Elvira, V. D.; Fisk, I.; Freeman, J.; Gottschalk, E.; Gray, L.; Green, D.; Grünendahl, S.; Gutsche, O.; Hare, D.; Harris, R. M.; Hasegawa, S.; Hirschauer, J.; Hu, Z.; Jayatilaka, B.; Jindariani, S.; Johnson, M.; Joshi, U.; Klima, B.; Kreis, B.; Lammel, S.; Linacre, J.; Lincoln, D.; Lipton, R.; Liu, M.; Liu, T.; Lopes De Sá, R.; Lykken, J.; Maeshima, K.; Magini, N.; Marraffino, J. M.; Maruyama, S.; Mason, D.; McBride, P.; Merkel, P.; Mrenna, S.; Nahn, S.; O'Dell, V.; Pedro, K.; Prokofyev, O.; Rakness, G.; Ristori, L.; Sexton-Kennedy, E.; Soha, A.; Spalding, W. J.; Spiegel, L.; Stoynev, S.; Strait, J.; Strobbe, N.; Taylor, L.; Tkaczyk, S.; Tran, N. V.; Uplegger, L.; Vaandering, E. W.; Vernieri, C.; Verzocchi, M.; Vidal, R.; Wang, M.; Weber, H. A.; Whitbeck, A.; Wu, Y.; Acosta, D.; Avery, P.; Bortignon, P.; Bourilkov, D.; Brinkerhoff, A.; Carnes, A.; Carver, M.; Curry, D.; Das, S.; Field, R. D.; Furic, I. K.; Konigsberg, J.; Korytov, A.; Low, J. F.; Ma, P.; Matchev, K.; Mei, H.; Mitselmakher, G.; Rank, D.; Shchutska, L.; Sperka, D.; Thomas, L.; Wang, J.; Wang, S.; Yelton, J.; Linn, S.; Markowitz, P.; Martinez, G.; Rodriguez, J. L.; Ackert, A.; Adams, T.; Askew, A.; Bein, S.; Hagopian, S.; Hagopian, V.; Johnson, K. F.; Prosper, H.; Santra, A.; Yohay, R.; Baarmand, M. M.; Bhopatkar, V.; Colafranceschi, S.; Hohlmann, M.; Noonan, D.; Roy, T.; Yumiceva, F.; Adams, M. R.; Apanasevich, L.; Berry, D.; Betts, R. R.; Bucinskaite, I.; Cavanaugh, R.; Evdokimov, O.; Gauthier, L.; Gerber, C. E.; Hofman, D. J.; Jung, K.; Sandoval Gonzalez, I. D.; Varelas, N.; Wang, H.; Wu, Z.; Zakaria, M.; Zhang, J.; Bilki, B.; Clarida, W.; Dilsiz, K.; Durgut, S.; Gandrajula, R. P.; Haytmyradov, M.; Khristenko, V.; Merlo, J.-P.; Mermerkaya, H.; Mestvirishvili, A.; Moeller, A.; Nachtman, J.; Ogul, H.; Onel, Y.; Ozok, F.; Penzo, A.; Snyder, C.; Tiras, E.; Wetzel, J.; Yi, K.; Anderson, I.; Blumenfeld, B.; Cocoros, A.; Eminizer, N.; Fehling, D.; Feng, L.; Gritsan, A. V.; Maksimovic, P.; Roskes, J.; Sarica, U.; Swartz, M.; Xiao, M.; Xin, Y.; You, C.; Al-bataineh, A.; Baringer, P.; Bean, A.; Boren, S.; Bowen, J.; Castle, J.; Forthomme, L.; Kenny, R. P.; Khalil, S.; Kropivnitskaya, A.; Majumder, D.; Mcbrayer, W.; Murray, M.; Sanders, S.; Stringer, R.; Takaki, J. D. Tapia; Wang, Q.; Ivanov, A.; Kaadze, K.; Maravin, Y.; Mohammadi, A.; Saini, L. K.; Skhirtladze, N.; Toda, S.; Rebassoo, F.; Wright, D.; Anelli, C.; Baden, A.; Baron, O.; Belloni, A.; Calvert, B.; Eno, S. C.; Ferraioli, C.; Gomez, J. A.; Hadley, N. J.; Jabeen, S.; Jeng, G. Y.; Kellogg, R. G.; Kolberg, T.; Kunkle, J.; Mignerey, A. C.; Ricci-Tam, F.; Shin, Y. H.; Skuja, A.; Tonjes, M. B.; Tonwar, S. C.; Abercrombie, D.; Allen, B.; Apyan, A.; Azzolini, V.; Barbieri, R.; Baty, A.; Bi, R.; Bierwagen, K.; Brandt, S.; Busza, W.; Cali, I. A.; D'Alfonso, M.; Demiragli, Z.; Di Matteo, L.; Gomez Ceballos, G.; Goncharov, M.; Hsu, D.; Iiyama, Y.; Innocenti, G. M.; Klute, M.; Kovalskyi, D.; Krajczar, K.; Lai, Y. S.; Lee, Y.-J.; Levin, A.; Luckey, P. D.; Maier, B.; Marini, A. C.; Mcginn, C.; Mironov, C.; Narayanan, S.; Niu, X.; Paus, C.; Roland, C.; Roland, G.; Salfeld-Nebgen, J.; Stephans, G. S. F.; Tatar, K.; Varma, M.; Velicanu, D.; Veverka, J.; Wang, J.; Wang, T. W.; Wyslouch, B.; Yang, M.; Benvenuti, A. C.; Chatterjee, R. M.; Evans, A.; Hansen, P.; Kalafut, S.; Kao, S. C.; Kubota, Y.; Lesko, Z.; Mans, J.; Nourbakhsh, S.; Ruckstuhl, N.; Rusack, R.; Tambe, N.; Turkewitz, J.; Acosta, J. G.; Oliveros, S.; Avdeeva, E.; Bloom, K.; Claes, D. R.; Fangmeier, C.; Gonzalez Suarez, R.; Kamalieddin, R.; Kravchenko, I.; Malta Rodrigues, A.; Meier, F.; Monroy, J.; Siado, J. E.; Snow, G. R.; Stieger, B.; Alyari, M.; Dolen, J.; Godshalk, A.; Harrington, C.; Iashvili, I.; Kaisen, J.; Nguyen, D.; Parker, A.; Rappoccio, S.; Roozbahani, B.; Alverson, G.; Barberis, E.; Hortiangtham, A.; Massironi, A.; Morse, D. M.; Nash, D.; Orimoto, T.; Teixeira De Lima, R.; Trocino, D.; Wang, R.-J.; Wood, D.; Bhattacharya, S.; Charaf, O.; Hahn, K. A.; Kumar, A.; Mucia, N.; Odell, N.; Pollack, B.; Schmitt, M. H.; Sung, K.; Trovato, M.; Velasco, M.; Dev, N.; Hildreth, M.; Hurtado Anampa, K.; Jessop, C.; Karmgard, D. J.; Kellams, N.; Lannon, K.; Marinelli, N.; Meng, F.; Mueller, C.; Musienko, Y.; Planer, M.; Reinsvold, A.; Ruchti, R.; Rupprecht, N.; Smith, G.; Taroni, S.; Wayne, M.; Wolf, M.; Woodard, A.; Alimena, J.; Antonelli, L.; Bylsma, B.; Durkin, L. S.; Flowers, S.; Francis, B.; Hart, A.; Hill, C.; Hughes, R.; Ji, W.; Liu, B.; Luo, W.; Puigh, D.; Winer, B. L.; Wulsin, H. W.; Cooperstein, S.; Driga, O.; Elmer, P.; Hardenbrook, J.; Hebda, P.; Lange, D.; Luo, J.; Marlow, D.; Medvedeva, T.; Mei, K.; Ojalvo, I.; Olsen, J.; Palmer, C.; Piroué, P.; Stickland, D.; Svyatkovskiy, A.; Tully, C.; Malik, S.; Barker, A.; Barnes, V. E.; Folgueras, S.; Gutay, L.; Jha, M. K.; Jones, M.; Jung, A. W.; Khatiwada, A.; Miller, D. H.; Neumeister, N.; Schulte, J. F.; Shi, X.; Sun, J.; Wang, F.; Xie, W.; Parashar, N.; Stupak, J.; Adair, A.; Akgun, B.; Chen, Z.; Ecklund, K. M.; Geurts, F. J. M.; Guilbaud, M.; Li, W.; Michlin, B.; Northup, M.; Padley, B. P.; Roberts, J.; Rorie, J.; Tu, Z.; Zabel, J.; Betchart, B.; Bodek, A.; de Barbaro, P.; Demina, R.; Duh, Y. t.; Ferbel, T.; Galanti, M.; Garcia-Bellido, A.; Han, J.; Hindrichs, O.; Khukhunaishvili, A.; Lo, K. H.; Tan, P.; Verzetti, M.; Agapitos, A.; Chou, J. P.; Gershtein, Y.; Gómez Espinosa, T. A.; Halkiadakis, E.; Heindl, M.; Hughes, E.; Kaplan, S.; Elayavalli, R. Kunnawalkam; Kyriacou, S.; Lath, A.; Nash, K.; Osherson, M.; Saka, H.; Salur, S.; Schnetzer, S.; Sheffield, D.; Somalwar, S.; Stone, R.; Thomas, S.; Thomassen, P.; Walker, M.; Delannoy, A. G.; Foerster, M.; Heideman, J.; Riley, G.; Rose, K.; Spanier, S.; Thapa, K.; Bouhali, O.; Celik, A.; Dalchenko, M.; De Mattia, M.; Delgado, A.; Dildick, S.; Eusebi, R.; Gilmore, J.; Huang, T.; Juska, E.; Kamon, T.; Mueller, R.; Pakhotin, Y.; Patel, R.; Perloff, A.; Perniè, L.; Rathjens, D.; Safonov, A.; Tatarinov, A.; Ulmer, K. A.; Akchurin, N.; Cowden, C.; Damgov, J.; De Guio, F.; Dragoiu, C.; Dudero, P. R.; Faulkner, J.; Gurpinar, E.; Kunori, S.; Lamichhane, K.; Lee, S. W.; Libeiro, T.; Peltola, T.; Undleeb, S.; Volobouev, I.; Wang, Z.; Greene, S.; Gurrola, A.; Janjam, R.; Johns, W.; Maguire, C.; Melo, A.; Ni, H.; Sheldon, P.; Tuo, S.; Velkovska, J.; Xu, Q.; Arenton, M. W.; Barria, P.; Cox, B.; Goodell, J.; Hirosky, R.; Ledovskoy, A.; Li, H.; Neu, C.; Sinthuprasith, T.; Sun, X.; Wang, Y.; Wolfe, E.; Xia, F.; Clarke, C.; Harr, R.; Karchin, P. E.; Sturdy, J.; Belknap, D. A.; Buchanan, J.; Caillol, C.; Dasu, S.; Dodd, L.; Duric, S.; Gomber, B.; Grothe, M.; Herndon, M.; Hervé, A.; Klabbers, P.; Lanaro, A.; Levine, A.; Long, K.; Loveless, R.; Perry, T.; Pierro, G. A.; Polese, G.; Ruggles, T.; Savin, A.; Smith, N.; Smith, W. H.; Taylor, D.; Woods, N.
2017-07-01
A search is presented for extra spatial dimensions, quantum black holes, and quark contact interactions in measurements of dijet angular distributions in proton-proton collisions at √{s}=13 TeV. The data were collected with the CMS detector at the LHC and correspond to an integrated luminosity of 2.6 fb-1. The distributions are found to be in agreement with predictions from perturbative quantum chromodynamics that include electroweak corrections. Limits for different contact interaction models are obtained. In a benchmark model, valid to next-to-leading order in QCD and in which only left-handed quarks participate, quark contact interactions are excluded up to a scale of 11.5 and 14.7 TeV for destructive or constructive interference, respectively. The production of quantum black holes is excluded for masses below 7.8 or 5.3 TeV, depending on the model. The lower limits for the scales of virtual graviton exchange in the Arkani-Hamed-Dimopoulos-Dvali model of extra spatial dimensions are in the range 7.9-11.2 TeV, and are the most stringent set of limits available.
Sirunyan, Albert M.
2017-07-05
A search is presented for extra spatial dimensions, quantum black holes, and quark contact interactions in measurements of dijet angular distributions in proton-proton collisions at √s = 13 TeV. The data were collected with the CMS detector at the LHC and correspond to an integrated luminosity of 2.6 fb –1. The distributions are found to be in agreement with predictions from perturbative quantum chromodynamics that include electroweak corrections. Limits for different contact interaction models are obtained in a benchmark model, valid to next-to-leading order in QCD, in which only left-handed quarks participate, with quark contact interactions excluded up to amore » scale of 11.5 or 14.7 TeV for destructive or constructive interference, respectively. The production of quantum black holes is excluded for masses below 7.8 or 5.3 TeV, depending on the model. Finally, the lower limits for the scales of virtual graviton exchange in the Arkani-Hamed--Dimopoulos--Dvali model of extra spatial dimensions are in the range 7.9-11.2 TeV, and are the most stringent set of limits available.« less
Craig, Erin M.; Stricker, Jonathan; Gardel, Margaret L.; Mogilner, Alex
2015-01-01
Cell motility relies on the continuous reorganization of a dynamic actin-myosin-adhesion network at the leading edge of the cell, in order to generate protrusion at the leading edge and traction between the cell and its external environment. We analyze experimentally measured spatial distributions of actin flow, traction force, myosin density, and adhesion density in control and pharmacologically perturbed epithelial cells in order to develop a mechanical model of the actin-adhesion-myosin self-organization at the leading edge. A model in which the F-actin network is treated as a viscous gel, and adhesion clutch engagement is strengthened by myosin but weakened by actin flow, can explain the measured molecular distributions and correctly predict the spatial distributions of the actin flow and traction stress. We test the model by comparing its predictions with measurements of the actin flow and traction stress in cells with fast and slow actin polymerization rates. The model predicts how the location of the lamellipodium-lamellum boundary depends on the actin viscosity and adhesion strength. The model further predicts that the location of the lamellipodium-lamellum boundary is not very sensitive to the level of myosin contraction. PMID:25969948
Malyarenko, Dariya I; Ross, Brian D; Chenevert, Thomas L
2014-03-01
Gradient nonlinearity of MRI systems leads to spatially dependent b-values and consequently high non-uniformity errors (10-20%) in apparent diffusion coefficient (ADC) measurements over clinically relevant field-of-views. This work seeks practical correction procedure that effectively reduces observed ADC bias for media of arbitrary anisotropy in the fewest measurements. All-inclusive bias analysis considers spatial and time-domain cross-terms for diffusion and imaging gradients. The proposed correction is based on rotation of the gradient nonlinearity tensor into the diffusion gradient frame where spatial bias of b-matrix can be approximated by its Euclidean norm. Correction efficiency of the proposed procedure is numerically evaluated for a range of model diffusion tensor anisotropies and orientations. Spatial dependence of nonlinearity correction terms accounts for the bulk (75-95%) of ADC bias for FA = 0.3-0.9. Residual ADC non-uniformity errors are amplified for anisotropic diffusion. This approximation obviates need for full diffusion tensor measurement and diagonalization to derive a corrected ADC. Practical scenarios are outlined for implementation of the correction on clinical MRI systems. The proposed simplified correction algorithm appears sufficient to control ADC non-uniformity errors in clinical studies using three orthogonal diffusion measurements. The most efficient reduction of ADC bias for anisotropic medium is achieved with non-lab-based diffusion gradients. Copyright © 2013 Wiley Periodicals, Inc.
Analysis and correction of gradient nonlinearity bias in ADC measurements
Malyarenko, Dariya I.; Ross, Brian D.; Chenevert, Thomas L.
2013-01-01
Purpose Gradient nonlinearity of MRI systems leads to spatially-dependent b-values and consequently high non-uniformity errors (10–20%) in ADC measurements over clinically relevant field-of-views. This work seeks practical correction procedure that effectively reduces observed ADC bias for media of arbitrary anisotropy in the fewest measurements. Methods All-inclusive bias analysis considers spatial and time-domain cross-terms for diffusion and imaging gradients. The proposed correction is based on rotation of the gradient nonlinearity tensor into the diffusion gradient frame where spatial bias of b-matrix can be approximated by its Euclidean norm. Correction efficiency of the proposed procedure is numerically evaluated for a range of model diffusion tensor anisotropies and orientations. Results Spatial dependence of nonlinearity correction terms accounts for the bulk (75–95%) of ADC bias for FA = 0.3–0.9. Residual ADC non-uniformity errors are amplified for anisotropic diffusion. This approximation obviates need for full diffusion tensor measurement and diagonalization to derive a corrected ADC. Practical scenarios are outlined for implementation of the correction on clinical MRI systems. Conclusions The proposed simplified correction algorithm appears sufficient to control ADC non-uniformity errors in clinical studies using three orthogonal diffusion measurements. The most efficient reduction of ADC bias for anisotropic medium is achieved with non-lab-based diffusion gradients. PMID:23794533
Local blur analysis and phase error correction method for fringe projection profilometry systems.
Rao, Li; Da, Feipeng
2018-05-20
We introduce a flexible error correction method for fringe projection profilometry (FPP) systems in the presence of local blur phenomenon. Local blur caused by global light transport such as camera defocus, projector defocus, and subsurface scattering will cause significant systematic errors in FPP systems. Previous methods, which adopt high-frequency patterns to separate the direct and global components, fail when the global light phenomenon occurs locally. In this paper, the influence of local blur on phase quality is thoroughly analyzed, and a concise error correction method is proposed to compensate the phase errors. For defocus phenomenon, this method can be directly applied. With the aid of spatially varying point spread functions and local frontal plane assumption, experiments show that the proposed method can effectively alleviate the system errors and improve the final reconstruction accuracy in various scenes. For a subsurface scattering scenario, if the translucent object is dominated by multiple scattering, the proposed method can also be applied to correct systematic errors once the bidirectional scattering-surface reflectance distribution function of the object material is measured.
Donnelly, Aoife; Naughton, Owen; Misstear, Bruce; Broderick, Brian
2016-10-14
This article describes a new methodology for increasing the spatial representativeness of individual monitoring sites. Air pollution levels at a given point are influenced by emission sources in the immediate vicinity. Since emission sources are rarely uniformly distributed around a site, concentration levels will inevitably be most affected by the sources in the prevailing upwind direction. The methodology provides a means of capturing this effect and providing additional information regarding source/pollution relationships. The methodology allows for the division of the air quality data from a given monitoring site into a number of sectors or wedges based on wind direction and estimation of annual mean values for each sector, thus optimising the information that can be obtained from a single monitoring station. The method corrects for short-term data, diurnal and seasonal variations in concentrations (which can produce uneven weighting of data within each sector) and uneven frequency of wind directions. Significant improvements in correlations between the air quality data and the spatial air quality indicators were obtained after application of the correction factors. This suggests the application of these techniques would be of significant benefit in land-use regression modelling studies. Furthermore, the method was found to be very useful for estimating long-term mean values and wind direction sector values using only short-term monitoring data. The methods presented in this article can result in cost savings through minimising the number of monitoring sites required for air quality studies while also capturing a greater degree of variability in spatial characteristics. In this way, more reliable, but also more expensive monitoring techniques can be used in preference to a higher number of low-cost but less reliable techniques. The methods described in this article have applications in local air quality management, source receptor analysis, land-use regression mapping and modelling and population exposure studies.
Brown, Jason L; Bennett, Joseph R; French, Connor M
2017-01-01
SDMtoolbox 2.0 is a software package for spatial studies of ecology, evolution, and genetics. The release of SDMtoolbox 2.0 allows researchers to use the most current ArcGIS software and MaxEnt software, and reduces the amount of time that would be spent developing common solutions. The central aim of this software is to automate complicated and repetitive spatial analyses in an intuitive graphical user interface. One core tenant facilitates careful parameterization of species distribution models (SDMs) to maximize each model's discriminatory ability and minimize overfitting. This includes carefully processing of occurrence data, environmental data, and model parameterization. This program directly interfaces with MaxEnt, one of the most powerful and widely used species distribution modeling software programs, although SDMtoolbox 2.0 is not limited to species distribution modeling or restricted to modeling in MaxEnt. Many of the SDM pre- and post-processing tools have 'universal' analogs for use with any modeling software. The current version contains a total of 79 scripts that harness the power of ArcGIS for macroecology, landscape genetics, and evolutionary studies. For example, these tools allow for biodiversity quantification (such as species richness or corrected weighted endemism), generation of least-cost paths and corridors among shared haplotypes, assessment of the significance of spatial randomizations, and enforcement of dispersal limitations of SDMs projected into future climates-to only name a few functions contained in SDMtoolbox 2.0. Lastly, dozens of generalized tools exists for batch processing and conversion of GIS data types or formats, which are broadly useful to any ArcMap user.
Scarciglia, Fabio; Barca, Donatella
2017-04-01
The dynamic behavior and inherent spatial heterogeneity, at different hierarchic levels, of the soil system often make the spatial distribution of potentially toxic metals (PTMs) quite complex and difficult to assess correctly. This work demonstrates that the application of laser ablation spectrometry (LA-ICP-MS) to soil thin sections constitutes an ancillary powerful tool to well-established analytical methods for tracing the behavior and fate of potential soil contaminants at the microsite level. It allowed to discriminate the contribution of PTMs in distinct soil sub-components, such as parent rock fragments, neoformed, clay-enriched or humified matrix, and specific pedogenetic features of illuvial origin (unstained or iron-stained clay coatings) even at very low contents. PTMs were analyzed in three soil profiles located in the Muravera area (Sardinia, Italy), where several, now abandoned mines were exploited. Recurrent trends of increase of many PTMs from rock to pedogenic matrix and to illuvial clay coatings, traced by LA-ICP-MS compositional data, revealed a pedogenetic control on metal fractionation and distribution, based on adsorption properties of clay minerals, iron oxyhydroxides or organic matter, and downprofile illuviation processes. The main PTMs patterns coupled with SEM-EDS analyses suggest that heavy metal-bearing mineral grains were sourced from the mine plants, in addition to the natural sedimentary input. The interplay between soil-forming processes and geomorphic dynamics significantly contributed to the PTMs spatial distribution detected in the different pedogenetic horizons and soil features.
Uniform competency-based local feature extraction for remote sensing images
NASA Astrophysics Data System (ADS)
Sedaghat, Amin; Mohammadi, Nazila
2018-01-01
Local feature detectors are widely used in many photogrammetry and remote sensing applications. The quantity and distribution of the local features play a critical role in the quality of the image matching process, particularly for multi-sensor high resolution remote sensing image registration. However, conventional local feature detectors cannot extract desirable matched features either in terms of the number of correct matches or the spatial and scale distribution in multi-sensor remote sensing images. To address this problem, this paper proposes a novel method for uniform and robust local feature extraction for remote sensing images, which is based on a novel competency criterion and scale and location distribution constraints. The proposed method, called uniform competency (UC) local feature extraction, can be easily applied to any local feature detector for various kinds of applications. The proposed competency criterion is based on a weighted ranking process using three quality measures, including robustness, spatial saliency and scale parameters, which is performed in a multi-layer gridding schema. For evaluation, five state-of-the-art local feature detector approaches, namely, scale-invariant feature transform (SIFT), speeded up robust features (SURF), scale-invariant feature operator (SFOP), maximally stable extremal region (MSER) and hessian-affine, are used. The proposed UC-based feature extraction algorithms were successfully applied to match various synthetic and real satellite image pairs, and the results demonstrate its capability to increase matching performance and to improve the spatial distribution. The code to carry out the UC feature extraction is available from href="https://www.researchgate.net/publication/317956777_UC-Feature_Extraction.
Species distribution models predict temporal but not spatial variation in forest growth.
van der Maaten, Ernst; Hamann, Andreas; van der Maaten-Theunissen, Marieke; Bergsma, Aldo; Hengeveld, Geerten; van Lammeren, Ron; Mohren, Frits; Nabuurs, Gert-Jan; Terhürne, Renske; Sterck, Frank
2017-04-01
Bioclimate envelope models have been widely used to illustrate the discrepancy between current species distributions and their potential habitat under climate change. However, the realism and correct interpretation of such projections has been the subject of considerable discussion. Here, we investigate whether climate suitability predictions correlate to tree growth, measured in permanent inventory plots and inferred from tree-ring records. We use the ensemble classifier RandomForest and species occurrence data from ~200,000 inventory plots to build species distribution models for four important European forestry species: Norway spruce, Scots pine, European beech, and pedunculate oak. We then correlate climate-based habitat suitability with volume measurements from ~50-year-old stands, available from ~11,000 inventory plots. Secondly, habitat projections based on annual historical climate are compared with ring width from ~300 tree-ring chronologies. Our working hypothesis is that habitat suitability projections from species distribution models should to some degree be associated with temporal or spatial variation in these growth records. We find that the habitat projections are uncorrelated with spatial growth records (inventory plot data), but they do predict interannual variation in tree-ring width, with an average correlation of .22. Correlation coefficients for individual chronologies range from values as high as .82 or as low as -.31. We conclude that tree responses to projected climate change are highly site-specific and that local suitability of a species for reforestation is difficult to predict. That said, projected increase or decrease in climatic suitability may be interpreted as an average expectation of increased or reduced growth over larger geographic scales.
Mechanisms of attention in reading parafoveal words: a cross-linguistic study in children.
Siéroff, Eric; Dahmen, Riadh; Fagard, Jacqueline
2012-05-01
The right visual field superiority (RVFS) for words may be explained by the cerebral lateralization for language, the scanning habits in relation to script direction, and spatial attention. The present study explored the influence of spatial attention on the RVFS in relation to scanning habits in school-age children. French second- and fourth-graders identified briefly presented French parafoveal words. Tunisian second- and fourth-graders identified Arabic words, and Tunisian fourth-graders identified French words. The distribution of spatial attention was evaluated by using a distracter in the visual field opposite the word. The results of the correct identification score showed that reading direction had only a partial effect on the identification of parafoveal words and the distribution of attention, with a clear RVFS and a larger effect of the distracter in the left visual field in French children reading French words, and an absence of asymmetry when Tunisian children read Arabic words. Fourth-grade Tunisian children also showed an RVFS when reading French words without an asymmetric distribution of attention, suggesting that their native language may have partially influenced reading strategies in the newly learned language. However, the mode of letter processing, evaluated by a qualitative error score, was only influenced by reading direction, with more sequential processing in the visual field where reading "begins." The distribution of attention when reading parafoveal words is better explained by the interaction between left hemisphere activation and strategies related to reading direction. We discuss these results in light of an attentional theory that dissociates selection and preparation.
Eugenio, Francisco; Marcello, Javier; Martin, Javier; Rodríguez-Esparragón, Dionisio
2017-11-16
Remote multispectral data can provide valuable information for monitoring coastal water ecosystems. Specifically, high-resolution satellite-based imaging systems, as WorldView-2 (WV-2), can generate information at spatial scales needed to implement conservation actions for protected littoral zones. However, coastal water-leaving radiance arriving at the space-based sensor is often small as compared to reflected radiance. In this work, complex approaches, which usually use an accurate radiative transfer code to correct the atmospheric effects, such as FLAASH, ATCOR and 6S, have been implemented for high-resolution imagery. They have been assessed in real scenarios using field spectroradiometer data. In this context, the three approaches have achieved excellent results and a slightly superior performance of 6S model-based algorithm has been observed. Finally, for the mapping of benthic habitats in shallow-waters marine protected environments, a relevant application of the proposed atmospheric correction combined with an automatic deglinting procedure is presented. This approach is based on the integration of a linear mixing model of benthic classes within the radiative transfer model of the water. The complete methodology has been applied to selected ecosystems in the Canary Islands (Spain) but the obtained results allow the robust mapping of the spatial distribution and density of seagrass in coastal waters and the analysis of multitemporal variations related to the human activity and climate change in littoral zones.
Eugenio, Francisco; Marcello, Javier; Martin, Javier
2017-01-01
Remote multispectral data can provide valuable information for monitoring coastal water ecosystems. Specifically, high-resolution satellite-based imaging systems, as WorldView-2 (WV-2), can generate information at spatial scales needed to implement conservation actions for protected littoral zones. However, coastal water-leaving radiance arriving at the space-based sensor is often small as compared to reflected radiance. In this work, complex approaches, which usually use an accurate radiative transfer code to correct the atmospheric effects, such as FLAASH, ATCOR and 6S, have been implemented for high-resolution imagery. They have been assessed in real scenarios using field spectroradiometer data. In this context, the three approaches have achieved excellent results and a slightly superior performance of 6S model-based algorithm has been observed. Finally, for the mapping of benthic habitats in shallow-waters marine protected environments, a relevant application of the proposed atmospheric correction combined with an automatic deglinting procedure is presented. This approach is based on the integration of a linear mixing model of benthic classes within the radiative transfer model of the water. The complete methodology has been applied to selected ecosystems in the Canary Islands (Spain) but the obtained results allow the robust mapping of the spatial distribution and density of seagrass in coastal waters and the analysis of multitemporal variations related to the human activity and climate change in littoral zones. PMID:29144444
Two-photon laser-induced fluorescence of atomic hydrogen in a diamond-depositing dc arcjet.
Juchmann, Wolfgang; Luque, Jorge; Jeffries, Jay B
2005-11-01
Atomic hydrogen in the plume of a dc-arcjet plasma is monitored by use of two-photon excited laser-induced fluorescence (LIF) during the deposition of diamond film. The effluent of a dc-arc discharge in hydrogen and argon forms a luminous plume as it flows through a converging-diverging nozzle into a reactor. When a trace of methane (< 2%) is added to the flow in the diverging part of the nozzle, diamond thin film grows on a water-cooled molybdenum substrate from the reactive mixture. LIF of atomic hydrogen in the arcjet plume is excited to the 3S and 3D levels with two photons near 205 nm, and the subsequent fluorescence is observed at Balmer-alpha near 656 nm. Spatially resolved LIF measurements of atomic hydrogen are made as a function of the ratio of hydrogen to argon feedstock gas, methane addition, and reactor pressure. At lower reactor pressures, time-resolved LIF measurements are used to verify our collisional quenching correction algorithm. The quenching rate coefficients for collisions with the major species in the arcjet (Ar, H, and H2) do not change with gas temperature variations in the plume (T < 2300 K). Corrections of the LIF intensity measurements for the spatial variation of collisional quenching are important to determine relative distributions of the atomic hydrogen concentration. The relative atomic hydrogen concentrations measured here are calibrated with an earlier calorimetric determination of the feedstock hydrogen dissociation to provide quantitative hydrogen-atom concentration distributions.
NASA Astrophysics Data System (ADS)
Correia, Carlos M.; Bond, Charlotte Z.; Sauvage, Jean-François; Fusco, Thierry; Conan, Rodolphe; Wizinowich, Peter L.
2017-10-01
We build on a long-standing tradition in astronomical adaptive optics (AO) of specifying performance metrics and error budgets using linear systems modeling in the spatial-frequency domain. Our goal is to provide a comprehensive tool for the calculation of error budgets in terms of residual temporally filtered phase power spectral densities and variances. In addition, the fast simulation of AO-corrected point spread functions (PSFs) provided by this method can be used as inputs for simulations of science observations with next-generation instruments and telescopes, in particular to predict post-coronagraphic contrast improvements for planet finder systems. We extend the previous results and propose the synthesis of a distributed Kalman filter to mitigate both aniso-servo-lag and aliasing errors whilst minimizing the overall residual variance. We discuss applications to (i) analytic AO-corrected PSF modeling in the spatial-frequency domain, (ii) post-coronagraphic contrast enhancement, (iii) filter optimization for real-time wavefront reconstruction, and (iv) PSF reconstruction from system telemetry. Under perfect knowledge of wind velocities, we show that $\\sim$60 nm rms error reduction can be achieved with the distributed Kalman filter embodying anti- aliasing reconstructors on 10 m class high-order AO systems, leading to contrast improvement factors of up to three orders of magnitude at few ${\\lambda}/D$ separations ($\\sim1-5{\\lambda}/D$) for a 0 magnitude star and reaching close to one order of magnitude for a 12 magnitude star.
NASA Technical Reports Server (NTRS)
Schlesinger, R. E.
1985-01-01
The impact of upstream-biased corrections for third-order spatial truncation error on the stability and phase error of the two-dimensional Crowley combined advective scheme with the cross-space term included is analyzed, putting primary emphasis on phase error reduction. The various versions of the Crowley scheme are formally defined, and their stability and phase error characteristics are intercompared using a linear Fourier component analysis patterned after Fromm (1968, 1969). The performances of the schemes under prototype simulation conditions are tested using time-dependent numerical experiments which advect an initially cone-shaped passive scalar distribution in each of three steady nondivergent flows. One such flow is solid rotation, while the other two are diagonal uniform flow and a strongly deformational vortex.
NASA Astrophysics Data System (ADS)
Sunar, Ulas; Rohrbach, Daniel; Morgan, Janet; Zeitouni, Natalie
2013-03-01
Photodynamic Therapy (PDT) has proven to be an effective treatment option for nonmelanoma skin cancers. The ability to quantify the concentration of drug in the treated area is crucial for effective treatment planning as well as predicting outcomes. We utilized spatial frequency domain imaging for quantifying the accurate concentration of protoporphyrin IX (PpIX) in phantoms and in vivo. We correct fluorescence against the effects of native tissue absorption and scattering parameters. First we quantified the absorption and scattering of the tissue non-invasively. Then, we corrected raw fluorescence signal by compensating for optical properties to get the absolute drug concentration. After phantom experiments, we used basal cell carcinoma (BCC) model in Gli mice to determine optical properties and drug concentration in vivo at pre-PDT.
NASA Astrophysics Data System (ADS)
Lee, Min Sun; Kim, Kyeong Yun; Ko, Guen Bae; Lee, Jae Sung
2017-05-01
In this study, we developed a proof-of-concept prototype PET system using a pair of depth-of-interaction (DOI) PET detectors based on the proposed DOI-encoding method and digital silicon photomultiplier (dSiPM). Our novel cost-effective DOI measurement method is based on a triangular-shaped reflector that requires only a single-layer pixelated crystal and single-ended signal readout. The DOI detector consisted of an 18 × 18 array of unpolished LYSO crystal (1.47 × 1.47 × 15 mm3) wrapped with triangular-shaped reflectors. The DOI information was encoded by depth-dependent light distribution tailored by the reflector geometry and DOI correction was performed using four-step depth calibration data and maximum-likelihood (ML) estimation. The detector pair and the object were placed on two motorized rotation stages to demonstrate 12-block ring PET geometry with 11.15 cm diameter. Spatial resolution was measured and phantom and animal imaging studies were performed to investigate imaging performance. All images were reconstructed with and without the DOI correction to examine the impact of our DOI measurement. The pair of dSiPM-based DOI PET detectors showed good physical performances respectively: 2.82 and 3.09 peak-to-valley ratios, 14.30% and 18.95% energy resolution, and 4.28 and 4.24 mm DOI resolution averaged over all crystals and all depths. A sub-millimeter spatial resolution was achieved at the center of the field of view (FOV). After applying ML-based DOI correction, maximum 36.92% improvement was achieved in the radial spatial resolution and a uniform resolution was observed within 5 cm of transverse PET FOV. We successfully acquired phantom and animal images with improved spatial resolution and contrast by using the DOI measurement. The proposed DOI-encoding method was successfully demonstrated in the system level and exhibited good performance, showing its feasibility for animal PET applications with high spatial resolution and sensitivity.
Hansen, Anja; Géneaux, Romain; Günther, Axel; Krüger, Alexander; Ripken, Tammo
2013-06-01
In femtosecond laser ophthalmic surgery tissue dissection is achieved by photodisruption based on laser induced optical breakdown. In order to minimize collateral damage to the eye laser surgery systems should be optimized towards the lowest possible energy threshold for photodisruption. However, optical aberrations of the eye and the laser system distort the irradiance distribution from an ideal profile which causes a rise in breakdown threshold energy even if great care is taken to minimize the aberrations of the system during design and alignment. In this study we used a water chamber with an achromatic focusing lens and a scattering sample as eye model and determined breakdown threshold in single pulse plasma transmission loss measurements. Due to aberrations, the precise lower limit for breakdown threshold irradiance in water is still unknown. Here we show that the threshold energy can be substantially reduced when using adaptive optics to improve the irradiance distribution by spatial beam shaping. We found that for initial aberrations with a root-mean-square wave front error of only one third of the wavelength the threshold energy can still be reduced by a factor of three if the aberrations are corrected to the diffraction limit by adaptive optics. The transmitted pulse energy is reduced by 17% at twice the threshold. Furthermore, the gas bubble motions after breakdown for pulse trains at 5 kilohertz repetition rate show a more transverse direction in the corrected case compared to the more spherical distribution without correction. Our results demonstrate how both applied and transmitted pulse energy could be reduced during ophthalmic surgery when correcting for aberrations. As a consequence, the risk of retinal damage by transmitted energy and the extent of collateral damage to the focal volume could be minimized accordingly when using adaptive optics in fs-laser surgery.
Hansen, Anja; Géneaux, Romain; Günther, Axel; Krüger, Alexander; Ripken, Tammo
2013-01-01
In femtosecond laser ophthalmic surgery tissue dissection is achieved by photodisruption based on laser induced optical breakdown. In order to minimize collateral damage to the eye laser surgery systems should be optimized towards the lowest possible energy threshold for photodisruption. However, optical aberrations of the eye and the laser system distort the irradiance distribution from an ideal profile which causes a rise in breakdown threshold energy even if great care is taken to minimize the aberrations of the system during design and alignment. In this study we used a water chamber with an achromatic focusing lens and a scattering sample as eye model and determined breakdown threshold in single pulse plasma transmission loss measurements. Due to aberrations, the precise lower limit for breakdown threshold irradiance in water is still unknown. Here we show that the threshold energy can be substantially reduced when using adaptive optics to improve the irradiance distribution by spatial beam shaping. We found that for initial aberrations with a root-mean-square wave front error of only one third of the wavelength the threshold energy can still be reduced by a factor of three if the aberrations are corrected to the diffraction limit by adaptive optics. The transmitted pulse energy is reduced by 17% at twice the threshold. Furthermore, the gas bubble motions after breakdown for pulse trains at 5 kilohertz repetition rate show a more transverse direction in the corrected case compared to the more spherical distribution without correction. Our results demonstrate how both applied and transmitted pulse energy could be reduced during ophthalmic surgery when correcting for aberrations. As a consequence, the risk of retinal damage by transmitted energy and the extent of collateral damage to the focal volume could be minimized accordingly when using adaptive optics in fs-laser surgery. PMID:23761849
Syfert, Mindy M; Smith, Matthew J; Coomes, David A
2013-01-01
Species distribution models (SDMs) trained on presence-only data are frequently used in ecological research and conservation planning. However, users of SDM software are faced with a variety of options, and it is not always obvious how selecting one option over another will affect model performance. Working with MaxEnt software and with tree fern presence data from New Zealand, we assessed whether (a) choosing to correct for geographical sampling bias and (b) using complex environmental response curves have strong effects on goodness of fit. SDMs were trained on tree fern data, obtained from an online biodiversity data portal, with two sources that differed in size and geographical sampling bias: a small, widely-distributed set of herbarium specimens and a large, spatially clustered set of ecological survey records. We attempted to correct for geographical sampling bias by incorporating sampling bias grids in the SDMs, created from all georeferenced vascular plants in the datasets, and explored model complexity issues by fitting a wide variety of environmental response curves (known as "feature types" in MaxEnt). In each case, goodness of fit was assessed by comparing predicted range maps with tree fern presences and absences using an independent national dataset to validate the SDMs. We found that correcting for geographical sampling bias led to major improvements in goodness of fit, but did not entirely resolve the problem: predictions made with clustered ecological data were inferior to those made with the herbarium dataset, even after sampling bias correction. We also found that the choice of feature type had negligible effects on predictive performance, indicating that simple feature types may be sufficient once sampling bias is accounted for. Our study emphasizes the importance of reducing geographical sampling bias, where possible, in datasets used to train SDMs, and the effectiveness and essentialness of sampling bias correction within MaxEnt.
Evaluate error correction ability of magnetorheological finishing by smoothing spectral function
NASA Astrophysics Data System (ADS)
Wang, Jia; Fan, Bin; Wan, Yongjian; Shi, Chunyan; Zhuo, Bin
2014-08-01
Power Spectral Density (PSD) has been entrenched in optics design and manufacturing as a characterization of mid-high spatial frequency (MHSF) errors. Smoothing Spectral Function (SSF) is a newly proposed parameter that based on PSD to evaluate error correction ability of computer controlled optical surfacing (CCOS) technologies. As a typical deterministic and sub-aperture finishing technology based on CCOS, magnetorheological finishing (MRF) leads to MHSF errors inevitably. SSF is employed to research different spatial frequency error correction ability of MRF process. The surface figures and PSD curves of work-piece machined by MRF are presented. By calculating SSF curve, the correction ability of MRF for different spatial frequency errors will be indicated as a normalized numerical value.
Interpolating Non-Parametric Distributions of Hourly Rainfall Intensities Using Random Mixing
NASA Astrophysics Data System (ADS)
Mosthaf, Tobias; Bárdossy, András; Hörning, Sebastian
2015-04-01
The correct spatial interpolation of hourly rainfall intensity distributions is of great importance for stochastical rainfall models. Poorly interpolated distributions may lead to over- or underestimation of rainfall and consequently to wrong estimates of following applications, like hydrological or hydraulic models. By analyzing the spatial relation of empirical rainfall distribution functions, a persistent order of the quantile values over a wide range of non-exceedance probabilities is observed. As the order remains similar, the interpolation weights of quantile values for one certain non-exceedance probability can be applied to the other probabilities. This assumption enables the use of kernel smoothed distribution functions for interpolation purposes. Comparing the order of hourly quantile values over different gauges with the order of their daily quantile values for equal probabilities, results in high correlations. The hourly quantile values also show high correlations with elevation. The incorporation of these two covariates into the interpolation is therefore tested. As only positive interpolation weights for the quantile values assure a monotonically increasing distribution function, the use of geostatistical methods like kriging is problematic. Employing kriging with external drift to incorporate secondary information is not applicable. Nonetheless, it would be fruitful to make use of covariates. To overcome this shortcoming, a new random mixing approach of spatial random fields is applied. Within the mixing process hourly quantile values are considered as equality constraints and correlations with elevation values are included as relationship constraints. To profit from the dependence of daily quantile values, distribution functions of daily gauges are used to set up lower equal and greater equal constraints at their locations. In this way the denser daily gauge network can be included in the interpolation of the hourly distribution functions. The applicability of this new interpolation procedure will be shown for around 250 hourly rainfall gauges in the German federal state of Baden-Württemberg. The performance of the random mixing technique within the interpolation is compared to applicable kriging methods. Additionally, the interpolation of kernel smoothed distribution functions is compared with the interpolation of fitted parametric distributions.
Using GIS databases for simulated nightlight imagery
NASA Astrophysics Data System (ADS)
Zollweg, Joshua D.; Gartley, Michael; Roskovensky, John; Mercier, Jeffery
2012-06-01
Proposed is a new technique for simulating nighttime scenes with realistically-modelled urban radiance. While nightlight imagery is commonly used to measure urban sprawl,1 it is uncommon to use urbanization as metric to develop synthetic nighttime scenes. In the developed methodology, the open-source Open Street Map (OSM) Geographic Information System (GIS) database is used. The database is comprised of many nodes, which are used to dene the position of dierent types of streets, buildings, and other features. These nodes are the driver used to model urban nightlights, given several assumptions. The rst assumption is that the spatial distribution of nodes is closely related to the spatial distribution of nightlights. Work by Roychowdhury et al has demonstrated the relationship between urban lights and development. 2 So, the real assumption being made is that the density of nodes corresponds to development, which is reasonable. Secondly, the local density of nodes must relate directly to the upwelled radiance within the given locality. Testing these assumptions using Albuquerque and Indianapolis as example cities revealed that dierent types of nodes produce more realistic results than others. Residential street nodes oered the best performance for any single node type, among the types tested in this investigation. Other node types, however, still provide useful supplementary data. Using streets and buildings dened in the OSM database allowed automated generation of simulated nighttime scenes of Albuquerque and Indianapolis in the Digital Imaging and Remote Sensing Image Generation (DIRSIG) model. The simulation was compared to real data from the recently deployed National Polar-orbiting Operational Environmental Satellite System(NPOESS) Visible Infrared Imager Radiometer Suite (VIIRS) platform. As a result of the comparison, correction functions were used to correct for discrepancies between simulated and observed radiance. Future work will include investigating more advanced approaches for mapping the spatial extent of nightlights, based on the distribution of dierent node types in local neighbourhoods. This will allow the spectral prole of each region to be dynamically adjusted, in addition to simply modifying the magnitude of a single source type.
Gaudio, Jennifer L; Snowdon, Charles T
2008-11-01
Animals living in stable home ranges have many potential cues to locate food. Spatial and color cues are important for wild Callitrichids (marmosets and tamarins). Field studies have assigned the highest priority to distal spatial cues for determining the location of food resources with color cues serving as a secondary cue to assess relative ripeness, once a food source is located. We tested two hypotheses with captive cotton-top tamarins: (a) Tamarins will demonstrate higher rates of initial learning when rewarded for attending to spatial cues versus color cues. (b) Tamarins will show higher rates of correct responses when transferred from color cues to spatial cues than from spatial cues to color cues. The results supported both hypotheses. Tamarins rewarded based on spatial location made significantly more correct choices and fewer errors than tamarins rewarded based on color cues during initial learning. Furthermore, tamarins trained on color cues showed significantly increased correct responses and decreased errors when cues were reversed to reward spatial cues. Subsequent reversal to color cues induced a regression in performance. For tamarins spatial cues appear more salient than color cues in a foraging task. (PsycINFO Database Record (c) 2008 APA, all rights reserved).
Non-Local Diffusion of Energetic Electrons during Solar Flares
NASA Astrophysics Data System (ADS)
Bian, N. H.; Emslie, G.; Kontar, E.
2017-12-01
The transport of the energy contained in suprathermal electrons in solar flares plays a key role in our understanding of many aspects of flare physics, from the spatial distributions of hard X-ray emission and energy deposition in the ambient atmosphere to global energetics. Historically the transport of these particles has been largely treated through a deterministic approach, in which first-order secular energy loss to electrons in the ambient target is treated as the dominant effect, with second-order diffusive terms (in both energy and angle) generally being either treated as a small correction or even neglected. Here, we critically analyze this approach, and we show that spatial diffusion through pitch-angle scattering necessarily plays a very significant role in the transport of electrons. We further show that a satisfactory treatment of the diffusion process requires consideration of non-local effects, so that the electron flux depends not just on the local gradient of the electron distribution function but on the value of this gradient within an extended region encompassing a significant fraction of a mean free path. Our analysis applies generally to pitch-angle scattering by a variety of mechanisms, from Coulomb collisions to turbulent scattering. We further show that the spatial transport of electrons along the magnetic field of a flaring loop can be modeled as a Continuous Time Random Walk with velocity-dependent probability distribution functions of jump sizes and occurrences, both of which can be expressed in terms of the scattering mean free path.
NASA Astrophysics Data System (ADS)
Bogoni, M.; Lanzoni, S.; Putti, M.
2017-12-01
Floodplains, and rivers therein, constitute complex systems whose simulation involves modeling of hydrodynamic, morphodynamic, chemical, and biological processes which act over a wide range of time scales (from days to centuries) and affect each other. Self-formed floodplains are produced by the sedimentary processes associated with the migration of river bends and the formation of abandoned oxbow lakes consequent to the cutoff of mature meanders. The erosion and deposition processes at the banks lead to heterogeneities in the surface composition, thus the river may experience faster or slower migration rates depending on the spatial distribution of the erosional resistance. As a consequence, the past spatial configurations of the river (i.e. the migration history) play a key role in shaping the successive river paths.We recently published a paper addressing the modeling of meander morphodynamics over self-formed heterogeneous floodplain. Results show that the heterogeneity in floodplain composition associated with the formation of geomorphic units (i.e., scroll bars and oxbow lakes) and the choice of a reliable flow field model to drive channel migration are two fundamental ingredients for reproducing correctly the long-term morphodynamics of alluvial meanders. We compare numerically generated planforms obtained for different scenarios of floodplain heterogeneity to natural meandering paths, through half meander metrics and spatial distribution of channel curvatures. Statistical and spectral tools disclose the complexity embedded in meandering geometry and the crucial differences between apparently similar configurations.Floodplain heterogeneity affects both the temporal and spatial distributions of meander geometry, and eventually leads to a closer statistical similarity between simulated and natural planform shapes when scroll bars and oxbow lakes left behind are harder to erode than the surrounding floodplain.
An Active Fire Temperature Retrieval Model Using Hyperspectral Remote Sensing
NASA Astrophysics Data System (ADS)
Quigley, K. W.; Roberts, D. A.; Miller, D.
2017-12-01
Wildfire is both an important ecological process and a dangerous natural threat that humans face. In situ measurements of wildfire temperature are notoriously difficult to collect due to dangerous conditions. Imaging spectrometry data has the potential to provide some of the most accurate and highest temporally-resolved active fire temperature retrieval information for monitoring and modeling. Recent studies on fire temperature retrieval have used have used Multiple Endmember Spectral Mixture Analysis applied to Airborne Visible applied to Airborne Visible / Infrared Imaging Spectrometer (AVIRIS) bands to model fire temperatures within the regions marked to contain fire, but these methods are less effective at coarser spatial resolutions, as linear mixing methods are degraded by saturation within the pixel. The assumption of a distribution of temperatures within pixels allows us to model pixels with an effective maximum and likely minimum temperature. This assumption allows a more robust approach to modeling temperature at different spatial scales. In this study, instrument-corrected radiance is forward-modeled for different ranges of temperatures, with weighted temperatures from an effective maximum temperature to a likely minimum temperature contributing to the total radiance of the modeled pixel. Effective maximum fire temperature is estimated by minimizing the Root Mean Square Error (RMSE) between modeled and measured fires. The model was tested using AVIRIS collected over the 2016 Sherpa Fire in Santa Barbara County, California,. While only in situ experimentation would be able to confirm active fire temperatures, the fit of the data to modeled radiance can be assessed, as well as the similarity in temperature distributions seen on different spatial resolution scales. Results show that this model improves upon current modeling methods in producing similar effective temperatures on multiple spatial scales as well as a similar modeled area distribution of those temperatures.
Precipitation From a Multiyear Database of Convection-Allowing WRF Simulations
NASA Astrophysics Data System (ADS)
Goines, D. C.; Kennedy, A. D.
2018-03-01
Convection-allowing models (CAMs) have become frequently used for operational forecasting and, more recently, have been utilized for general circulation model downscaling. CAM forecasts have typically been analyzed for a few case studies or over short time periods, but this limits the ability to judge the overall skill of deterministic simulations. Analysis over long time periods can yield a better understanding of systematic model error. Four years of warm season (April-August, 2010-2013)-simulated precipitation has been accumulated from two Weather Research and Forecasting (WRF) models with 4 km grid spacing. The simulations were provided by the National Center for Environmental Prediction (NCEP) and the National Severe Storms Laboratory (NSSL), each with different dynamic cores and parameterization schemes. These simulations are evaluated against the NCEP Stage-IV precipitation data set with similar 4 km grid spacing. The spatial distribution and diurnal cycle of precipitation in the central United States are analyzed using Hovmöller diagrams, grid point correlations, and traditional verification skill scoring (i.e., ETS; Equitable Threat Score). Although NCEP-WRF had a high positive error in total precipitation, spatial characteristics were similar to observations. For example, the spatial distribution of NCEP-WRF precipitation correlated better than NSSL-WRF for the Northern Plains. Hovmöller results exposed a delay in initiation and decay of diurnal precipitation by NCEP-WRF while both models had difficulty in reproducing the timing and location of propagating precipitation. ETS was highest for NSSL-WRF in all domains at all times. ETS was also higher in areas of propagating precipitation compared to areas of unorganized diurnal scattered precipitation. Monthly analysis identified unique differences between the two models in their abilities to correctly simulate the spatial distribution and zonal motion of precipitation through the warm season.
Library based x-ray scatter correction for dedicated cone beam breast CT
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shi, Linxi; Zhu, Lei, E-mail: leizhu@gatech.edu
Purpose: The image quality of dedicated cone beam breast CT (CBBCT) is limited by substantial scatter contamination, resulting in cupping artifacts and contrast-loss in reconstructed images. Such effects obscure the visibility of soft-tissue lesions and calcifications, which hinders breast cancer detection and diagnosis. In this work, we propose a library-based software approach to suppress scatter on CBBCT images with high efficiency, accuracy, and reliability. Methods: The authors precompute a scatter library on simplified breast models with different sizes using the GEANT4-based Monte Carlo (MC) toolkit. The breast is approximated as a semiellipsoid with homogeneous glandular/adipose tissue mixture. For scatter correctionmore » on real clinical data, the authors estimate the breast size from a first-pass breast CT reconstruction and then select the corresponding scatter distribution from the library. The selected scatter distribution from simplified breast models is spatially translated to match the projection data from the clinical scan and is subtracted from the measured projection for effective scatter correction. The method performance was evaluated using 15 sets of patient data, with a wide range of breast sizes representing about 95% of general population. Spatial nonuniformity (SNU) and contrast to signal deviation ratio (CDR) were used as metrics for evaluation. Results: Since the time-consuming MC simulation for library generation is precomputed, the authors’ method efficiently corrects for scatter with minimal processing time. Furthermore, the authors find that a scatter library on a simple breast model with only one input parameter, i.e., the breast diameter, sufficiently guarantees improvements in SNU and CDR. For the 15 clinical datasets, the authors’ method reduces the average SNU from 7.14% to 2.47% in coronal views and from 10.14% to 3.02% in sagittal views. On average, the CDR is improved by a factor of 1.49 in coronal views and 2.12 in sagittal views. Conclusions: The library-based scatter correction does not require increase in radiation dose or hardware modifications, and it improves over the existing methods on implementation simplicity and computational efficiency. As demonstrated through patient studies, the authors’ approach is effective and stable, and is therefore clinically attractive for CBBCT imaging.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Axente, Marian; Von Eyben, Rie; Hristov, Dimitre, E-mail: dimitre.hristov@stanford.edu
2015-03-15
Purpose: To clinically evaluate an iterative metal artifact reduction (IMAR) algorithm prototype in the radiation oncology clinic setting by testing for accuracy in CT number retrieval, relative dosimetric changes in regions affected by artifacts, and improvements in anatomical and shape conspicuity of corrected images. Methods: A phantom with known material inserts was scanned in the presence/absence of metal with different configurations of placement and sizes. The relative change in CT numbers from the reference data (CT with no metal) was analyzed. The CT studies were also used for dosimetric tests where dose distributions from both photon and proton beams weremore » calculated. Dose differences and gamma analysis were calculated to quantify the relative changes between doses calculated on the different CT studies. Data from eight patients (all different treatment sites) were also used to quantify the differences between dose distributions before and after correction with IMAR, with no reference standard. A ranking experiment was also conducted to analyze the relative confidence of physicians delineating anatomy in the near vicinity of the metal implants. Results: IMAR corrected images proved to accurately retrieve CT numbers in the phantom study, independent of metal insert configuration, size of the metal, and acquisition energy. For plastic water, the mean difference between corrected images and reference images was −1.3 HU across all scenarios (N = 37) with a 90% confidence interval of [−2.4, −0.2] HU. While deviations were relatively higher in images with more metal content, IMAR was able to effectively correct the CT numbers independent of the quantity of metal. Residual errors in the CT numbers as well as some induced by the correction algorithm were found in the IMAR corrected images. However, the dose distributions calculated on IMAR corrected images were closer to the reference data in phantom studies. Relative spatial difference in the dose distributions in the regions affected by the metal artifacts was also observed in patient data. However, in absence of a reference ground truth (CT set without metal inserts), these differences should not be interpreted as improvement/deterioration of the accuracy of calculated dose. With limited data presented, it was observed that proton dosimetry was affected more than photons as expected. Physicians were significantly more confident contouring anatomy in the regions affected by artifacts. While site specific preferences were detected, all indicated that they would consistently use IMAR corrected images. Conclusions: IMAR correction algorithm could be readily implemented in an existing clinical workflow upon commercial release. While residual errors still exist in IMAR corrected images, these images present with better overall conspicuity of the patient/phantom geometry and offer more accurate CT numbers for improved local dosimetry. The variety of different scenarios included herein attest to the utility of the evaluated IMAR for a wide range of radiotherapy clinical scenarios.« less
Saint-Aubin, Jean; Tremblay, Sébastien; Jalbert, Annie
2007-01-01
This research investigated the nature of encoding and its contribution to serial recall for visual-spatial information. In order to do so, we examined the relationship between fixation duration and recall performance. Using the dot task--a series of seven dots spatially distributed on a monitor screen is presented sequentially for immediate recall--performance and eye-tracking data were recorded during the presentation of the to-be-remembered items. When participants were free to move their eyes at their will, both fixation durations and probability of correct recall decreased as a function of serial position. Furthermore, imposing constant durations of fixation across all serial positions had a beneficial impact (though relatively small) on item but not order recall. Great care was taken to isolate the effect of fixation duration from that of presentation duration. Although eye movement at encoding contributes to immediate memory, it is not decisive in shaping serial recall performance. Our results also provide further evidence that the distinction between item and order information, well-established in the verbal domain, extends to visual-spatial information.
NASA Astrophysics Data System (ADS)
McElvain, Jon; Campbell, Scott P.; Miller, Jonathan; Jin, Elaine W.
2010-01-01
The dead leaves model was recently introduced as a method for measuring the spatial frequency response (SFR) of camera systems. The target consists of a series of overlapping opaque circles with a uniform gray level distribution and radii distributed as r-3. Unlike the traditional knife-edge target, the SFR derived from the dead leaves target will be penalized for systems that employ aggressive noise reduction. Initial studies have shown that the dead leaves SFR correlates well with sharpness/texture blur preference, and thus the target can potentially be used as a surrogate for more expensive subjective image quality evaluations. In this paper, the dead leaves target is analyzed for measurement of camera system spatial frequency response. It was determined that the power spectral density (PSD) of the ideal dead leaves target does not exhibit simple power law dependence, and scale invariance is only loosely obeyed. An extension to the ideal dead leaves PSD model is proposed, including a correction term to account for system noise. With this extended model, the SFR of several camera systems with a variety of formats was measured, ranging from 3 to 10 megapixels; the effects of handshake motion blur are also analyzed via the dead leaves target.
Cheng, Yu; Sayde, Chadi; Li, Qi; ...
2017-04-18
Taylors’ frozen turbulence hypothesis suggests that all turbulent eddies are advected by the mean streamwise velocity, without changes in their properties. This hypothesis has been widely invoked to compute Reynolds’ averaging using temporal turbulence data measured at a single point in space. However, in the atmospheric surface layer, the exact relationship between convection velocity and wavenumber k has not been fully revealed since previous observations were limited by either their spatial resolution or by the sampling length. Using Distributed Temperature Sensing (DTS), acquiring turbulent temperature fluctuations at high temporal and spatial frequencies, we computed convection velocities across wavenumbers using amore » phase spectrum method. We found that convection velocity decreases as k –1/3 at the higher wavenumbers of the inertial subrange instead of being independent of wavenumber as suggested by Taylor's hypothesis. We further corroborated this result using large eddy simulations. Applying Taylor's hypothesis thus systematically underestimates turbulent spectrum in the inertial subrange. As a result, a correction is proposed for point-based eddy-covariance measurements, which can improve surface energy budget closure and estimates of CO 2 fluxes.« less
A spatially distributed energy balance snowmelt model for application in mountain basins
Marks, D.; Domingo, J.; Susong, D.; Link, T.; Garen, D.
1999-01-01
Snowmelt is the principal source for soil moisture, ground-water re-charge, and stream-flow in mountainous regions of the western US, Canada, and other similar regions of the world. Information on the timing, magnitude, and contributing area of melt under variable or changing climate conditions is required for successful water and resource management. A coupled energy and mass-balance model ISNOBAL is used to simulate the development and melting of the seasonal snowcover in several mountain basins in California, Idaho, and Utah. Simulations are done over basins varying from 1 to 2500 km2, with simulation periods varying from a few days for the smallest basin, Emerald Lake watershed in California, to multiple snow seasons for the Park City area in Utah. The model is driven by topographically corrected estimates of radiation, temperature, humidity, wind, and precipitation. Simulation results in all basins closely match independently measured snow water equivalent, snow depth, or runoff during both the development and depletion of the snowcover. Spatially distributed estimates of snow deposition and melt allow us to better understand the interaction between topographic structure, climate, and moisture availability in mountain basins of the western US. Application of topographically distributed models such as this will lead to improved water resource and watershed management.Snowmelt is the principal source for soil moisture, ground-water re-charge, and stream-flow in mountainous regions of the western US, Canada, and other similar regions of the world. Information on the timing, magnitude, and contributing area of melt under variable or changing climate conditions is required for successful water and resource management. A coupled energy and mass-balance model ISNOBAL is used to simulate the development and melting of the seasonal snowcover in several mountain basins in California, Idaho, and Utah. Simulations are done over basins varying from 1 to 2500 km2, with simulation periods varying from a few days for the smallest basin, Emerald Lake watershed in California, to multiple snow seasons for the Park City area in Utah. The model is driven by topographically corrected estimates of radiation, temperature, humidity, wind, and precipitation. Simulation results in all basins closely match independently measured snow water equivalent, snow depth, or runoff during both the development and depletion of the snowcover. Spatially distributed estimates of snow deposition and melt allow us to better understand the interaction between topographic structure, climate, and moisture availability in mountain basins of the western US. Application of topographically distributed models such as this will lead to improved water resource and watershed management.
Performance evaluation of spatial compounding in the presence of aberration and adaptive imaging
NASA Astrophysics Data System (ADS)
Dahl, Jeremy J.; Guenther, Drake; Trahey, Gregg E.
2003-05-01
Spatial compounding has been used for years to reduce speckle in ultrasonic images and to resolve anatomical features hidden behind the grainy appearance of speckle. Adaptive imaging restores image contrast and resolution by compensating for beamforming errors caused by tissue-induced phase errors. Spatial compounding represents a form of incoherent imaging, whereas adaptive imaging attempts to maintain a coherent, diffraction-limited aperture in the presence of aberration. Using a Siemens Antares scanner, we acquired single channel RF data on a commercially available 1-D probe. Individual channel RF data was acquired on a cyst phantom in the presence of a near field electronic phase screen. Simulated data was also acquired for both a 1-D and a custom built 8x96, 1.75-D probe (Tetrad Corp.). The data was compounded using a receive spatial compounding algorithm; a widely used algorithm because it takes advantage of parallel beamforming to avoid reductions in frame rate. Phase correction was also performed by using a least mean squares algorithm to estimate the arrival time errors. We present simulation and experimental data comparing the performance of spatial compounding to phase correction in contrast and resolution tasks. We evaluate spatial compounding and phase correction, and combinations of the two methods, under varying aperture sizes, aperture overlaps, and aberrator strength to examine the optimum configuration and conditions in which spatial compounding will provide a similar or better result than adaptive imaging. We find that, in general, phase correction is hindered at high aberration strengths and spatial frequencies, whereas spatial compounding is helped by these aberrators.
Spectral and Spatial Analysis of Volatile Deposits in Io's Loki Patera
NASA Astrophysics Data System (ADS)
Landis, C. E.; Howell, R. R.
2012-12-01
Loki Patera is an active volcanic feature approximately 200 km in diameter on Jupiter's moon Io. The goals of this research are to better understand the nature of volatile distribution in and around the Loki region. Images taken by Voyager I show a number of bright features distributed across the patera surface. These features, referred to as "bergs," may be fumaroles which allow sulfur gases from the lava beneath the hardened crust to escape onto the surface. By examining the spatial distribution of the bergs and the spectral signatures of bergs and other features around Loki Patera, we can better understand their role in the volcanic activity observed at Loki, and perhaps elsewhere on Io. Spectral data from the Voyager and Galileo missions were examined using ISIS3, a program suite developed by the USGS. Photometric corrections were applied to the images to adjust for changes in lighting geometry. The spatial distribution of the bergs was examined using ArcMap. Initial results indicate that the bergs seldom occur near the inner and outer edges of the patera, which are known to be hotter than other parts of the patera. The lack of bergs in this area suggests that thermal properties of the crust may control the distribution of the bergs. The spacing of the bergs, which on average are about 6 km from each other, and other distribution statistics are used to test whether there is some maximum area of crust in which one berg can accommodate the escaping gases. The spectral signatures of the bergs themselves are compared to other surface features in and around the patera. Further study of the bergs and other features will continue to shed light on the underlying geologic and volcanic processes responsible for the activity at Loki. This work was supported in part by NASA JDAP grant NNX09AE06G.
Leistedt, B.; Peiris, H. V.; Elsner, F.; ...
2016-10-17
Spatially-varying depth and characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, in particular in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. Wemore » illustrate the complementarity of these two approaches by comparing the SV data with the BCC-UFig, a synthetic sky catalogue generated by forward-modelling of the DES SV images. We then analyse the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially-varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and well-captured by the maps of observing conditions. The combined use of the maps, the SV data and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak lensing analyses. However, they will need to be carefully characterised in upcoming phases of DES in order to avoid biasing the inferred cosmological results. The framework presented is relevant to all multi-epoch surveys, and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null-tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Leistedt, B.; Peiris, H. V.; Elsner, F.
Spatially varying depth and the characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, particularly in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES-SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. Wemore » illustrate the complementary nature of these two approaches by comparing the SV data with BCC-UFig, a synthetic sky catalog generated by forward-modeling of the DES-SV images. We analyze the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and are well-captured by the maps of observing conditions. The combined use of the maps, the SV data, and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak-lensing analyses. However, they will need to be carefully characterized in upcoming phases of DES in order to avoid biasing the inferred cosmological results. The framework presented here is relevant to all multi-epoch surveys and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Leistedt, B.; Peiris, H. V.; Elsner, F.
Spatially-varying depth and characteristics of observing conditions, such as seeing, airmass, or sky background, are major sources of systematic uncertainties in modern galaxy survey analyses, in particular in deep multi-epoch surveys. We present a framework to extract and project these sources of systematics onto the sky, and apply it to the Dark Energy Survey (DES) to map the observing conditions of the Science Verification (SV) data. The resulting distributions and maps of sources of systematics are used in several analyses of DES SV to perform detailed null tests with the data, and also to incorporate systematics in survey simulations. Wemore » illustrate the complementarity of these two approaches by comparing the SV data with the BCC-UFig, a synthetic sky catalogue generated by forward-modelling of the DES SV images. We then analyse the BCC-UFig simulation to construct galaxy samples mimicking those used in SV galaxy clustering studies. We show that the spatially-varying survey depth imprinted in the observed galaxy densities and the redshift distributions of the SV data are successfully reproduced by the simulation and well-captured by the maps of observing conditions. The combined use of the maps, the SV data and the BCC-UFig simulation allows us to quantify the impact of spatial systematics on N(z), the redshift distributions inferred using photometric redshifts. We conclude that spatial systematics in the SV data are mainly due to seeing fluctuations and are under control in current clustering and weak lensing analyses. However, they will need to be carefully characterised in upcoming phases of DES in order to avoid biasing the inferred cosmological results. The framework presented is relevant to all multi-epoch surveys, and will be essential for exploiting future surveys such as the Large Synoptic Survey Telescope, which will require detailed null-tests and realistic end-to-end image simulations to correctly interpret the deep, high-cadence observations of the sky.« less
Continuous rainfall simulation for regional flood risk assessment - application in the Austrian Alps
NASA Astrophysics Data System (ADS)
Salinas, Jose Luis; Nester, Thomas; Komma, Jürgen; Blöschl, Günter
2017-04-01
Generation of realistic synthetic spatial rainfall is of pivotal importance for assessing regional hydroclimatic hazard as the input for long term rainfall-runoff simulations. The correct reproduction of the observed rainfall characteristics, such as regional intensity-duration-frequency curves, is necessary to adequately model the magnitude and frequency of the flood peaks. Furthermore, the replication of the observed rainfall spatial and temporal correlations allows to model important other hydrological features like antecedent soil moisture conditions before extreme rainfall events. In this work, we present an application in the Tirol region (Austrian alps) of a modification of the model presented by Bardossy and Platte (1992), where precipitation is modeled on a station basis as a mutivariate autoregressive model (mAr) in a Normal space, and then transformed to a Gamma-distributed space. For the sake of simplicity, the parameters of the Gamma distributions are assumed to vary monthly according to a sinusoidal function, and are calibrated trying to simultaneously reproduce i) mean annual rainfall, ii) mean daily rainfall amounts, iii) standard deviations of daily rainfall amounts, and iv) 24-hours intensity duration frequency curve. The calibration of the spatial and temporal correlation parameters is performed in a way that the intensity-duration-frequency curves aggregated at different spatial and temporal scales reproduce the measured ones. Bardossy, A., and E. J. Plate (1992), Space-time model for daily rainfall using atmospheric circulation patterns, Water Resour. Res., 28(5), 1247-1259, doi:10.1029/91WR02589.
Magnetorheological Finishing for Imprinting Continuous Phase Plate Structure onto Optical Surfaces
DOE Office of Scientific and Technical Information (OSTI.GOV)
Menapace, J A; Dixit, S N; Genin, F Y
2004-01-05
Magnetorheological finishing (MRF) techniques have been developed to manufacture continuous phase plates (CPP's) and custom phase corrective structures on polished fused silica surfaces. These phase structures are important for laser applications requiring precise manipulation and control of beam-shape, energy distribution, and wavefront profile. The MRF's unique deterministic-sub-aperture polishing characteristics make it possible to imprint complex topographical information onto optical surfaces at spatial scale-lengths approaching 1 mm. In this study, we present the results of experiments and model calculations that explore imprinting two-dimensional sinusoidal structures. Results show how the MRF removal function impacts and limits imprint fidelity and what must bemore » done to arrive at a high quality surface. We also present several examples of this imprinting technology for fabrication of phase correction plates and CPPs for use at high fluences.« less
Bennett, Joseph R.; French, Connor M.
2017-01-01
SDMtoolbox 2.0 is a software package for spatial studies of ecology, evolution, and genetics. The release of SDMtoolbox 2.0 allows researchers to use the most current ArcGIS software and MaxEnt software, and reduces the amount of time that would be spent developing common solutions. The central aim of this software is to automate complicated and repetitive spatial analyses in an intuitive graphical user interface. One core tenant facilitates careful parameterization of species distribution models (SDMs) to maximize each model’s discriminatory ability and minimize overfitting. This includes carefully processing of occurrence data, environmental data, and model parameterization. This program directly interfaces with MaxEnt, one of the most powerful and widely used species distribution modeling software programs, although SDMtoolbox 2.0 is not limited to species distribution modeling or restricted to modeling in MaxEnt. Many of the SDM pre- and post-processing tools have ‘universal’ analogs for use with any modeling software. The current version contains a total of 79 scripts that harness the power of ArcGIS for macroecology, landscape genetics, and evolutionary studies. For example, these tools allow for biodiversity quantification (such as species richness or corrected weighted endemism), generation of least-cost paths and corridors among shared haplotypes, assessment of the significance of spatial randomizations, and enforcement of dispersal limitations of SDMs projected into future climates—to only name a few functions contained in SDMtoolbox 2.0. Lastly, dozens of generalized tools exists for batch processing and conversion of GIS data types or formats, which are broadly useful to any ArcMap user. PMID:29230356
FRESHEM - Fresh-saline groundwater distribution in Zeeland (NL) derived from airborne EM
NASA Astrophysics Data System (ADS)
Siemon, Bernhard; van Baaren, Esther; Dabekaussen, Willem; Delsman, Joost; Gunnik, Jan; Karaoulis, Marios; de Louw, Perry; Oude Essink, Gualbert; Pauw, Pieter; Steuer, Annika; Meyer, Uwe
2017-04-01
In a setting of predominantly saline surface waters, the availability of fresh water for agricultural purposes is not obvious in Zeeland, The Netherlands. Canals and ditches are mainly brackish to saline due to saline seepage, which originates from old marine deposits and salt-water transgressions during historical times. The only available fresh groundwater is present in the form of freshwater lenses floating on top of the saline groundwater. This fresh groundwater is vital for agricultural, industrial, ecological, water conservation and drinking water functions. An essential first step for managing this fresh groundwater properly is to know the present spatial fresh-brackish-saline groundwater distribution. As traditional salinity monitoring is labour-intensive, airborne electromagnetics (AEM), which is fast and can cover large areas in short time, is an efficient alternative. A consortium of BGR, Deltares and TNO started FRESHEM Zeeland (FREsh Salt groundwater distribution by Helicopter ElectroMagnetic survey in the Province of Zeeland) in October 2014. Within 3x2 weeks of the first project year, the entire area of about 2000 km2 was surveyed using BGR's helicopter-borne geophysical system totalling to about 10,000 line-km. The HEM datasets of 17 subareas were carefully processed using advanced BGR in-house software and inverted to 2.5 Million resistivity-depth models. Ground truthing demonstrated that the large-scale HEM results fit very well with small-scale ground EM data (ECPT). Based on this spatial resistivity distribution, a 3D voxel model for Chloride concentration was derived for the entire province taking into account geological model data (GeoTOP) for the lithology correction and local in-situ groundwater measurements for the translation of water conductivity to Chloride concentration. The 3D voxel model enables stakeholders to implement spatial Chloride concentration in their groundwater models.
A Critical Assessment of Officially Reported Chagas Disease Surveillance Data in Mexico
Shelly, Ellen M.; Acuna-Soto, Rodolfo; Ernst, Kacey C.; Sterling, Charles R.
2016-01-01
Objective Chagas disease, a disease caused by Trypanosoma cruzi, disproportionately affects poor people throughout Latin America. In Mexico, assessments of officially reported burden have not been previously reported. To evaluate discontinuity between surveillance data and data from other sources, we used data from the Mexican Ministry of Health to describe the distribution of reported Chagas disease over time in Mexico and compare it with estimates from the literature. Methods We summarized age and sex differences for Chagas cases and mortality for 1995–2013 and 1982–2010, respectively. We examined the spatial distribution of Chagas disease over time with respect to disease burden. We further compared officially reported figures with estimates from the literature. Results Among 6,494 officially reported cases, rates of Chagas disease were highest in adults aged 25–44 years (47.3%). Mortality was highest in adults aged ≥45 years (423/495, 85.5%). The data indicated increasing temporal trends for incidence and mortality. The greatest burden occurred in southern states, with increasing spatial distribution over time. Fewer than 900 cases and 40 deaths were officially reported annually, in contrast to estimates from the literature of approximately 69,000 new cases and 25,000 deaths annually. Conclusion While increasing trends in officially reported data have been observed, large discrepancies in case estimates compromise our understanding of Chagas disease epidemiology. Reported cases based on current practices are not enough to correctly assess the Chagas disease burden and spatial distribution in Mexico. Understanding the true epidemiology of this disease will lead to more focused and successful control and prevention strategies to decrease disease burden. PMID:26843671
Solving for the Surface: An Automated Approach to THEMIS Atmospheric Correction
NASA Astrophysics Data System (ADS)
Ryan, A. J.; Salvatore, M. R.; Smith, R.; Edwards, C. S.; Christensen, P. R.
2013-12-01
Here we present the initial results of an automated atmospheric correction algorithm for the Thermal Emission Imaging System (THEMIS) instrument, whereby high spectral resolution Thermal Emission Spectrometer (TES) data are queried to generate numerous atmospheric opacity values for each THEMIS infrared image. While the pioneering methods of Bandfield et al. [2004] also used TES spectra to atmospherically correct THEMIS data, the algorithm presented here is a significant improvement because of the reduced dependency on user-defined inputs for individual images. Additionally, this technique is particularly useful for correcting THEMIS images that have captured a range of atmospheric conditions and/or surface elevations, issues that have been difficult to correct for using previous techniques. Thermal infrared observations of the Martian surface can be used to determine the spatial distribution and relative abundance of many common rock-forming minerals. This information is essential to understanding the planet's geologic and climatic history. However, the Martian atmosphere also has absorptions in the thermal infrared which complicate the interpretation of infrared measurements obtained from orbit. TES has sufficient spectral resolution (143 bands at 10 cm-1 sampling) to linearly unmix and remove atmospheric spectral end-members from the acquired spectra. THEMIS has the benefit of higher spatial resolution (~100 m/pixel vs. 3x5 km/TES-pixel) but has lower spectral resolution (8 surface sensitive spectral bands). As such, it is not possible to isolate the surface component by unmixing the atmospheric contribution from the THEMIS spectra, as is done with TES. Bandfield et al. [2004] developed a technique using atmospherically corrected TES spectra as tie-points for constant radiance offset correction and surface emissivity retrieval. This technique is the primary method used to correct THEMIS but is highly susceptible to inconsistent results if great care in the selection of TES spectra is not exercised. Our algorithm implements a newly populated TES database that was created using PostgreSQL/PostGIS geospatial database. TES pixels that meet user-defined quality criteria and that intersect a THEMIS observation of interest may be quickly retrieved using this new database. The THEMIS correction process [Bandfield et al. 2004] is then run using all TES pixels that pass an additional set of TES-THEMIS relational quality checks. The result is a spatially correlated set of atmospheric opacity values, determined from the difference between each atmospherically corrected TES pixel and the overlapping portion of the THEMIS image. The dust and ice contributions to the atmospheric opacity are estimated using known dust and ice spectral dependencies [Smith et al. 2003]. These opacity values may be used to determine atmospheric variation across the scene, from which topography- and temperature-scaled atmospheric contribution may be calculated and removed. References: Bandfield, JL et al. [2004], JGR 109, E10008. Smith, MD et al. [2003], JGR 108, E11, 5115.
InSAR Tropospheric Correction Methods: A Statistical Comparison over Different Regions
NASA Astrophysics Data System (ADS)
Bekaert, D. P.; Walters, R. J.; Wright, T. J.; Hooper, A. J.; Parker, D. J.
2015-12-01
Observing small magnitude surface displacements through InSAR is highly challenging, and requires advanced correction techniques to reduce noise. In fact, one of the largest obstacles facing the InSAR community is related to tropospheric noise correction. Spatial and temporal variations in temperature, pressure, and relative humidity result in a spatially-variable InSAR tropospheric signal, which masks smaller surface displacements due to tectonic or volcanic deformation. Correction methods applied today include those relying on weather model data, GNSS and/or spectrometer data. Unfortunately, these methods are often limited by the spatial and temporal resolution of the auxiliary data. Alternatively a correction can be estimated from the high-resolution interferometric phase by assuming a linear or a power-law relationship between the phase and topography. For these methods, the challenge lies in separating deformation from tropospheric signals. We will present results of a statistical comparison of the state-of-the-art tropospheric corrections estimated from spectrometer products (MERIS and MODIS), a low and high spatial-resolution weather model (ERA-I and WRF), and both the conventional linear and power-law empirical methods. We evaluate the correction capability over Southern Mexico, Italy, and El Hierro, and investigate the impact of increasing cloud cover on the accuracy of the tropospheric delay estimation. We find that each method has its strengths and weaknesses, and suggest that further developments should aim to combine different correction methods. All the presented methods are included into our new open source software package called TRAIN - Toolbox for Reducing Atmospheric InSAR Noise (Bekaert et al., in review), which is available to the community Bekaert, D., R. Walters, T. Wright, A. Hooper, and D. Parker (in review), Statistical comparison of InSAR tropospheric correction techniques, Remote Sensing of Environment
NASA Astrophysics Data System (ADS)
Inoue, Makoto; Morino, Isamu; Uchino, Osamu; Nakatsuru, Takahiro; Yoshida, Yukio; Yokota, Tatsuya; Wunch, Debra; Wennberg, Paul O.; Roehl, Coleen M.; Griffith, David W. T.; Velazco, Voltaire A.; Deutscher, Nicholas M.; Warneke, Thorsten; Notholt, Justus; Robinson, John; Sherlock, Vanessa; Hase, Frank; Blumenstock, Thomas; Rettinger, Markus; Sussmann, Ralf; Kyrö, Esko; Kivi, Rigel; Shiomi, Kei; Kawakami, Shuji; De Mazière, Martine; Arnold, Sabrina G.; Feist, Dietrich G.; Barrow, Erica A.; Barney, James; Dubey, Manvendra; Schneider, Matthias; Iraci, Laura T.; Podolske, James R.; Hillyard, Patrick W.; Machida, Toshinobu; Sawa, Yousuke; Tsuboi, Kazuhiro; Matsueda, Hidekazu; Sweeney, Colm; Tans, Pieter P.; Andrews, Arlyn E.; Biraud, Sebastien C.; Fukuyama, Yukio; Pittman, Jasna V.; Kort, Eric A.; Tanaka, Tomoaki
2016-08-01
We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO2 (XCO2) and CH4 (XCH4) derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT). We conduct correlation analyses between the GOSAT biases and simultaneously retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from the Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the uncorrected/corrected GOSAT data were compared to independent XCO2 and XCH4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole-to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically derived bias correction improves the agreement between GOSAT XCO2/XCH4 and the aircraft data. Finally, we present spatial distributions and temporal variations of the derived GOSAT biases.
Adjustment of spatio-temporal precipitation patterns in a high Alpine environment
NASA Astrophysics Data System (ADS)
Herrnegger, Mathew; Senoner, Tobias; Nachtnebel, Hans-Peter
2018-01-01
This contribution presents a method for correcting the spatial and temporal distribution of precipitation fields in a mountainous environment. The approach is applied within a flood forecasting model in the Upper Enns catchment in the Central Austrian Alps. Precipitation exhibits a large spatio-temporal variability in Alpine areas. Additionally the density of the monitoring network is low and measurements are subjected to major errors. This can lead to significant deficits in water balance estimation and stream flow simulations, e.g. for flood forecasting models. Therefore precipitation correction factors are frequently applied. For the presented study a multiplicative, stepwise linear correction model is implemented in the rainfall-runoff model COSERO to adjust the precipitation pattern as a function of elevation. To account for the local meteorological conditions, the correction model is derived for two elevation zones: (1) Valley floors to 2000 m a.s.l. and (2) above 2000 m a.s.l. to mountain peaks. Measurement errors also depend on the precipitation type, with higher magnitudes in winter months during snow fall. Therefore, additionally, separate correction factors for winter and summer months are estimated. Significant improvements in the runoff simulations could be achieved, not only in the long-term water balance simulation and the overall model performance, but also in the simulation of flood peaks.
Altomare, Cristina; Guglielmann, Raffaella; Riboldi, Marco; Bellazzi, Riccardo; Baroni, Guido
2015-02-01
In high precision photon radiotherapy and in hadrontherapy, it is crucial to minimize the occurrence of geometrical deviations with respect to the treatment plan in each treatment session. To this end, point-based infrared (IR) optical tracking for patient set-up quality assessment is performed. Such tracking depends on external fiducial points placement. The main purpose of our work is to propose a new algorithm based on simulated annealing and augmented Lagrangian pattern search (SAPS), which is able to take into account prior knowledge, such as spatial constraints, during the optimization process. The SAPS algorithm was tested on data related to head and neck and pelvic cancer patients, and that were fitted with external surface markers for IR optical tracking applied for patient set-up preliminary correction. The integrated algorithm was tested considering optimality measures obtained with Computed Tomography (CT) images (i.e. the ratio between the so-called target registration error and fiducial registration error, TRE/FRE) and assessing the marker spatial distribution. Comparison has been performed with randomly selected marker configuration and with the GETS algorithm (Genetic Evolutionary Taboo Search), also taking into account the presence of organs at risk. The results obtained with SAPS highlight improvements with respect to the other approaches: (i) TRE/FRE ratio decreases; (ii) marker distribution satisfies both marker visibility and spatial constraints. We have also investigated how the TRE/FRE ratio is influenced by the number of markers, obtaining significant TRE/FRE reduction with respect to the random configurations, when a high number of markers is used. The SAPS algorithm is a valuable strategy for fiducial configuration optimization in IR optical tracking applied for patient set-up error detection and correction in radiation therapy, showing that taking into account prior knowledge is valuable in this optimization process. Further work will be focused on the computational optimization of the SAPS algorithm toward fast point-of-care applications. Copyright © 2014 Elsevier Inc. All rights reserved.
Combustion distribution control using the extremum seeking algorithm
NASA Astrophysics Data System (ADS)
Marjanovic, A.; Krstic, M.; Djurovic, Z.; Kvascev, G.; Papic, V.
2014-12-01
Quality regulation of the combustion process inside the furnace is the basis of high demands for increasing robustness, safety and efficiency of thermal power plants. The paper considers the possibility of spatial temperature distribution control inside the boiler, based on the correction of distribution of coal over the mills. Such control system ensures the maintenance of the flame focus away from the walls of the boiler, and thus preserves the equipment and reduces the possibility of ash slugging. At the same time, uniform heat dissipation over mills enhances the energy efficiency of the boiler, while reducing the pollution of the system. A constrained multivariable extremum seeking algorithm is proposed as a tool for combustion process optimization with the main objective of centralizing the flame in the furnace. Simulations are conducted on a model corresponding to the 350MW boiler of the Nikola Tesla Power Plant, in Obrenovac, Serbia.
Cunningham, Charles H; Dominguez Viqueira, William; Hurd, Ralph E; Chen, Albert P
2014-02-01
Blip-reversed echo-planar imaging (EPI) is investigated as a method for measuring and correcting the spatial shifts that occur due to bulk frequency offsets in (13)C metabolic imaging in vivo. By reversing the k-space trajectory for every other time point, the direction of the spatial shift for a given frequency is reversed. Here, mutual information is used to find the 'best' alignment between images and thereby measure the frequency offset. Time-resolved 3D images of pyruvate/lactate/urea were acquired with 5 s temporal resolution over a 1 min duration in rats (N = 6). For each rat, a second injection was performed with the demodulation frequency purposely mis-set by +35 Hz, to test the correction for erroneous shifts in the images. Overall, the shift induced by the 35 Hz frequency offset was 5.9 ± 0.6 mm (mean ± standard deviation). This agrees well with the expected 5.7 mm shift based on the 2.02 ms delay between k-space lines (giving 30.9 Hz per pixel). The 0.6 mm standard deviation in the correction corresponds to a frequency-detection accuracy of 4 Hz. A method was presented for ensuring the spatial registration between (13)C metabolic images and conventional anatomical images when long echo-planar readouts are used. The frequency correction method was shown to have an accuracy of 4 Hz. Summing the spatially corrected frames gave a signal-to-noise ratio (SNR) improvement factor of 2 or greater, compared with the highest single frame. Copyright © 2013 John Wiley & Sons, Ltd.
NASA Astrophysics Data System (ADS)
Smith, Tony E.; Lee, Ka Lok
2012-01-01
There is a common belief that the presence of residual spatial autocorrelation in ordinary least squares (OLS) regression leads to inflated significance levels in beta coefficients and, in particular, inflated levels relative to the more efficient spatial error model (SEM). However, our simulations show that this is not always the case. Hence, the purpose of this paper is to examine this question from a geometric viewpoint. The key idea is to characterize the OLS test statistic in terms of angle cosines and examine the geometric implications of this characterization. Our first result is to show that if the explanatory variables in the regression exhibit no spatial autocorrelation, then the distribution of test statistics for individual beta coefficients in OLS is independent of any spatial autocorrelation in the error term. Hence, inferences about betas exhibit all the optimality properties of the classic uncorrelated error case. However, a second more important series of results show that if spatial autocorrelation is present in both the dependent and explanatory variables, then the conventional wisdom is correct. In particular, even when an explanatory variable is statistically independent of the dependent variable, such joint spatial dependencies tend to produce "spurious correlation" that results in over-rejection of the null hypothesis. The underlying geometric nature of this problem is clarified by illustrative examples. The paper concludes with a brief discussion of some possible remedies for this problem.
Adhikari, Bhim M; Sathian, K; Epstein, Charles M; Lamichhane, Bidhan; Dhamala, Mukesh
2014-05-01
Oscillatory interactions within functionally specialized but distributed brain regions are believed to be central to perceptual and cognitive functions. Here, using human scalp electroencephalography (EEG) recordings combined with source reconstruction techniques, we study how oscillatory activity functionally organizes different neocortical regions during a tactile discrimination task near the limit of spatial acuity. While undergoing EEG recordings, blindfolded participants felt a linear three-dot array presented electromechanically, under computer control, and reported whether the central dot was offset to the left or right. The average brain response differed significantly for trials with correct and incorrect perceptual responses in the timeframe approximately between 130 and 175ms. During trials with correct responses, source-level peak activity appeared in the left primary somatosensory cortex (SI) at around 45ms, in the right lateral occipital complex (LOC) at 130ms, in the right posterior intraparietal sulcus (pIPS) at 160ms, and finally in the left dorsolateral prefrontal cortex (dlPFC) at 175ms. Spectral interdependency analysis of activity in these nodes showed two distinct distributed networks, a dominantly feedforward network in the beta band (12-30Hz) that included all four nodes and a recurrent network in the gamma band (30-100Hz) that linked SI, pIPS and dlPFC. Measures of network activity in both bands were correlated with the accuracy of task performance. These findings suggest that beta and gamma band oscillatory networks coordinate activity between neocortical regions mediating sensory and cognitive processing to arrive at tactile perceptual decisions. Copyright © 2014 The Authors. Published by Elsevier Inc. All rights reserved.
Insight into nuclear body formation of phytochromes through stochastic modelling and experiment.
Grima, Ramon; Sonntag, Sebastian; Venezia, Filippo; Kircher, Stefan; Smith, Robert W; Fleck, Christian
2018-05-01
Spatial relocalization of proteins is crucial for the correct functioning of living cells. An interesting example of spatial ordering is the light-induced clustering of plant photoreceptor proteins. Upon irradiation by white or red light, the red light-active phytochrome, phytochrome B, enters the nucleus and accumulates in large nuclear bodies. The underlying physical process of nuclear body formation remains unclear, but phytochrome B is thought to coagulate via a simple protein-protein binding process. We measure, for the first time, the distribution of the number of phytochrome B-containing nuclear bodies as well as their volume distribution. We show that the experimental data cannot be explained by a stochastic model of nuclear body formation via simple protein-protein binding processes using physically meaningful parameter values. Rather modelling suggests that the data is consistent with a two step process: a fast nucleation step leading to macroparticles followed by a subsequent slow step in which the macroparticles bind to form the nuclear body. An alternative explanation for the observed nuclear body distribution is that the phytochromes bind to a so far unknown molecular structure. We believe it is likely this result holds more generally for other nuclear body-forming plant photoreceptors and proteins. Creative Commons Attribution license.
Spatial trends in leaf size of Amazonian rainforest trees
NASA Astrophysics Data System (ADS)
Malhado, A. C. M.; Malhi, Y.; Whittaker, R. J.; Ladle, R. J.; Ter Steege, H.; Aragão, L. E. O. C.; Quesada, C. A.; Araujo-Murakami, A.; Phillips, O. L.; Peacock, J.; Lopez-Gonzalez, G.; Baker, T. R.; Butt, N.; Anderson, L. O.; Arroyo, L.; Almeida, S.; Higuchi, N.; Killeen, T. J.; Monteagudo, A.; Neill, D.; Pitman, N.; Prieto, A.; Salomão, R. P.; Silva, N.; Vásquez-Martínez, R.; Laurance, W. F.
2009-02-01
Leaf size influences many aspects of tree function such as rates of transpiration and photosynthesis and, consequently, often varies in a predictable way in response to environmental gradients. The recent development of pan-Amazonian databases based on permanent botanical plots (e.g. RAINFOR, ATDN) has now made it possible to assess trends in leaf size across environmental gradients in Amazonia. Previous plot-based studies have shown that the community structure of Amazonian trees breaks down into at least two major ecological gradients corresponding with variations in soil fertility (decreasing south to northeast) and length of the dry season (increasing from northwest to south and east). Here we describe the results of the geographic distribution of leaf size categories based on 121 plots distributed across eight South American countries. We find that, as predicted, the Amazon forest is predominantly populated by tree species and individuals in the mesophyll size class (20.25-182.25 cm2). The geographic distribution of species and individuals with large leaves (>20.25 cm2) is complex but is generally characterized by a higher proportion of such trees in the north-west of the region. Spatially corrected regressions reveal weak correlations between the proportion of large-leaved species and metrics of water availability. We also find a significant negative relationship between leaf size and wood density.
Spatial trends in leaf size of Amazonian rainforest trees
NASA Astrophysics Data System (ADS)
Malhado, A. C. M.; Malhi, Y.; Whittaker, R. J.; Ladle, R. J.; Ter Steege, H.; Phillips, O. L.; Butt, N.; Aragão, L. E. O. C.; Quesada, C. A.; Araujo-Murakami, A.; Arroyo, L.; Peacock, J.; Lopez-Gonzalez, G.; Baker, T. R.; Anderson, L. O.; Almeida, S.; Higuchi, N.; Killeen, T. J.; Monteagudo, A.; Neill, D.; Pitman, N.; Prieto, A.; Salomão, R. P.; Vásquez-Martínez, R.; Laurance, W. F.
2009-08-01
Leaf size influences many aspects of tree function such as rates of transpiration and photosynthesis and, consequently, often varies in a predictable way in response to environmental gradients. The recent development of pan-Amazonian databases based on permanent botanical plots has now made it possible to assess trends in leaf size across environmental gradients in Amazonia. Previous plot-based studies have shown that the community structure of Amazonian trees breaks down into at least two major ecological gradients corresponding with variations in soil fertility (decreasing from southwest to northeast) and length of the dry season (increasing from northwest to south and east). Here we describe the geographic distribution of leaf size categories based on 121 plots distributed across eight South American countries. We find that the Amazon forest is predominantly populated by tree species and individuals in the mesophyll size class (20.25-182.25 cm2). The geographic distribution of species and individuals with large leaves (>20.25 cm2) is complex but is generally characterized by a higher proportion of such trees in the northwest of the region. Spatially corrected regressions reveal weak correlations between the proportion of large-leaved species and metrics of water availability. We also find a significant negative relationship between leaf size and wood density.
Fire, humans, and climate: modeling distribution dynamics of boreal forest waterbirds.
Börger, Luca; Nudds, Thomas D
2014-01-01
Understanding the effects of landscape change and environmental variability on ecological processes is important for evaluating resource management policies, such as the emulation of natural forest disturbances. We analyzed time series of detection/nondetection data using hierarchical models in a Bayesian multi-model inference framework to decompose the dynamics of species distributions into responses to environmental variability, spatial variation in habitat conditions, and population dynamics and interspecific interactions, while correcting for observation errors and variation in sampling regimes. We modeled distribution dynamics of 14 waterbird species (broadly defined, including wetland and riparian species) using data from two different breeding bird surveys collected in the Boreal Shield ecozone within Ontario, Canada. Temporal variation in species occupancy (2000-2006) was primarily driven by climatic variability. Only two species showed evidence of consistent temporal trends in distribution: Ring-necked Duck (Aythya collaris) decreased, and Red-winged Blackbird (Agelaius phoeniceus) increased. The models had good predictive ability on independent data over time (1997-1999). Spatial variation in species occupancy was strongly related to the distribution of specific land cover types and habitat disturbance: Fire and forest harvesting influenced occupancy more than did roads, settlements, or mines. Bioclimatic and habitat heterogeneity indices and geographic coordinates exerted negligible influence on most species distributions. Estimated habitat suitability indices had good predictive ability on spatially independent data (Hudson Bay Lowlands ecozone). Additionally, we detected effects of interspecific interactions. Species responses to fire and forest harvesting were similar for 13 of 14 species; thus, forest-harvesting practices in Ontario generally appeared to emulate the effects of fire for waterbirds over timescales of 10-20 years. Extrapolating to all 84 waterbird species breeding on the Ontario Boreal Shield, however, suggested that up to 30 species may instead have altered (short-term) distribution dynamics due to forestry practices. Hence, natural disturbances are critical components of the ecology of the boreal forest and forest practices which aim to approximate them may succeed in allowing the maintenance of the associated species, but improved monitoring and modeling of large-scale boreal forest bird distribution dynamics will be necessary to resolve existing uncertainties, especially on less-common species.
Yothers, Mitchell P; Browder, Aaron E; Bumm, Lloyd A
2017-01-01
We have developed a real-space method to correct distortion due to thermal drift and piezoelectric actuator nonlinearities on scanning tunneling microscope images using Matlab. The method uses the known structures typically present in high-resolution atomic and molecularly resolved images as an internal standard. Each image feature (atom or molecule) is first identified in the image. The locations of each feature's nearest neighbors are used to measure the local distortion at that location. The local distortion map across the image is simultaneously fit to our distortion model, which includes thermal drift in addition to piezoelectric actuator hysteresis and creep. The image coordinates of the features and image pixels are corrected using an inverse transform from the distortion model. We call this technique the thermal-drift, hysteresis, and creep transform. Performing the correction in real space allows defects, domain boundaries, and step edges to be excluded with a spatial mask. Additional real-space image analyses are now possible with these corrected images. Using graphite(0001) as a model system, we show lattice fitting to the corrected image, averaged unit cell images, and symmetry-averaged unit cell images. Statistical analysis of the distribution of the image features around their best-fit lattice sites measures the aggregate noise in the image, which can be expressed as feature confidence ellipsoids.
NASA Astrophysics Data System (ADS)
Yothers, Mitchell P.; Browder, Aaron E.; Bumm, Lloyd A.
2017-01-01
We have developed a real-space method to correct distortion due to thermal drift and piezoelectric actuator nonlinearities on scanning tunneling microscope images using Matlab. The method uses the known structures typically present in high-resolution atomic and molecularly resolved images as an internal standard. Each image feature (atom or molecule) is first identified in the image. The locations of each feature's nearest neighbors are used to measure the local distortion at that location. The local distortion map across the image is simultaneously fit to our distortion model, which includes thermal drift in addition to piezoelectric actuator hysteresis and creep. The image coordinates of the features and image pixels are corrected using an inverse transform from the distortion model. We call this technique the thermal-drift, hysteresis, and creep transform. Performing the correction in real space allows defects, domain boundaries, and step edges to be excluded with a spatial mask. Additional real-space image analyses are now possible with these corrected images. Using graphite(0001) as a model system, we show lattice fitting to the corrected image, averaged unit cell images, and symmetry-averaged unit cell images. Statistical analysis of the distribution of the image features around their best-fit lattice sites measures the aggregate noise in the image, which can be expressed as feature confidence ellipsoids.
NASA Astrophysics Data System (ADS)
Feng, Jilu; Rogge, Derek; Rivard, Benoit
2018-02-01
This study investigates using the Airborne Hyperspectral Imaging Systems (AISA) visible and short-wave infrared (SWIR) and Spatially Enhanced Broadband Array Spectrograph System (SEBASS) longwave infrared (LWIR) (2 and 4 m spatial resolution, respectively) imagery independently and in combination to produce detailed lithologic maps in a subarctic region (Cape Smith Belt, Nunavik, Canada) where regionally metamorphosed lower greenschist mafic, ultramafic and sedimentary rocks are exposed in the presence of lichen coatings. We make use of continuous wavelet analysis (CWA) to improve the radiometric quality of the imagery through the minimization of random noise and the enhancement of spectral features, the minimization of residual errors in the ISAC radiometric correction and target temperature estimation in the case of the LWIR data, the minimization of line to line residual calibration effects that lead to inconsistencies in data mosaics, and the reduction in variability of the spectral continuum introduced by variable illumination and topography. The use of CWA also provides a platform to directly combine the wavelet scale spectral profiles of the SWIR and LWIR after applying a scalar correction factor to the LWIR such that the dynamic range of two data sets have equal weight. This is possible using CWA as the datasets are normalized to a zero mean allowing spectra from different spectral regions to be adjoined. Lithologic maps are generated using an iterative spectral unmixing approach with image spectral endmembers extracted from the SWIR and LWIR imagery based on locations defined from previous work of the study area and field mapping information. Unmixing results of the independent SWIR and LWIR data, and the combined data show clear benefits to using the CWA combined imagery. The analysis showed SWIR and LWIR imagery highlight similar regions and spatial distributions for the three ultramafic units (dunite, peridotite, pyroxenite). However, significant differences are observed for quartz-rich sediments, with the SWIR overestimating the distribution of these rocks whereas the LWIR provided more consistent results compared with existing maps. Both SWIR and LWIR imagery were impacted by the pervasive lichen coatings on the mafic rocks (basalts and gabbros), although the SWIR provided better results than the LWIR. Limitations observed for the independent data sets were removed using the combined spectral data resulting in all geologically meaningful units mapped correctly in comparison with existing geological maps.
NASA Astrophysics Data System (ADS)
Moghim, S.; Hsu, K.; Bras, R. L.
2013-12-01
General Circulation Models (GCMs) are used to predict circulation and energy transfers between the atmosphere and the land. It is known that these models produce biased results that will have impact on their uses. This work proposes a new method for bias correction: the equidistant cumulative distribution function-artificial neural network (EDCDFANN) procedure. The method uses artificial neural networks (ANNs) as a surrogate model to estimate bias-corrected temperature, given an identification of the system derived from GCM models output variables. A two-layer feed forward neural network is trained with observations during a historical period and then the adjusted network can be used to predict bias-corrected temperature for future periods. To capture the extreme values this method is combined with the equidistant CDF matching method (EDCDF, Li et al. 2010). The proposed method is tested with the Community Climate System Model (CCSM3) outputs using air and skin temperature, specific humidity, shortwave and longwave radiation as inputs to the ANN. This method decreases the mean square error and increases the spatial correlation between the modeled temperature and the observed one. The results indicate the EDCDFANN has potential to remove the biases of the model outputs.
Sumner, David M.; Pathak, Chandra S.; Mecikalski, John R.; Paech, Simon J.; Wu, Qinglong; Sangoyomi, Taiye; Babcock, Roger W.; Walton, Raymond
2008-01-01
Solar radiation data are critically important for the estimation of evapotranspiration. Analysis of visible-channel data derived from Geostationary Operational Environmental Satellites (GOES) using radiative transfer modeling has been used to produce spatially- and temporally-distributed datasets of solar radiation. An extensive network of (pyranometer) surface measurements of solar radiation in the State of Florida has allowed refined calibration of a GOES-derived daily integrated radiation data product. This refinement of radiation data allowed for corrections of satellite sensor drift, satellite generational change, and consideration of the highly-variable cloudy conditions that are typical of Florida. To aid in calibration of a GOES-derived radiation product, solar radiation data for the period 1995–2004 from 58 field stations that are located throughout the State were compiled. The GOES radiation product was calibrated by way of a three-step process: 1) comparison with ground-based pyranometer measurements on clear reference days, 2) correcting for a bias related to cloud cover, and 3) deriving month-by-month bias correction factors. Pre-calibration results indicated good model performance, with a station-averaged model error of 2.2 MJ m–2 day–1 (13 percent). Calibration reduced errors to 1.7 MJ m–2 day–1 (10 percent) and also removed time- and cloudiness-related biases. The final dataset has been used to produce Statewide evapotranspiration estimates.
NASA Astrophysics Data System (ADS)
Bertrand, Sophie; Díaz, Erich; Lengaigne, Matthieu
2008-10-01
Peruvian anchovy ( Engraulis ringens) stock abundance is tightly driven by the high and unpredictable variability of the Humboldt Current Ecosystem. Management of the fishery therefore cannot rely on mid- or long-term management policy alone but needs to be adaptive at relatively short time scales. Regular acoustic surveys are performed on the stock at intervals of 2 to 4 times a year, but there is a need for more time continuous monitoring indicators to ensure that management can respond at suitable time scales. Existing literature suggests that spatially explicit data on the location of fishing activities could be used as a proxy for target stock distribution. Spatially explicit commercial fishing data could therefore guide adaptive management decisions at shorter time scales than is possible through scientific stock surveys. In this study we therefore aim to (1) estimate the position of fishing operations for the entire fleet of Peruvian anchovy purse-seiners using the Peruvian satellite vessel monitoring system (VMS), and (2) quantify the extent to which the distribution of purse-seine sets describes anchovy distribution. To estimate fishing set positions from vessel tracks derived from VMS data we developed a methodology based on artificial neural networks (ANN) trained on a sample of fishing trips with known fishing set positions (exact fishing positions are known for approximately 1.5% of the fleet from an at-sea observer program). The ANN correctly identified 83% of the real fishing sets and largely outperformed comparative linear models. This network is then used to forecast fishing operations for those trips where no observers were onboard. To quantify the extent to which fishing set distribution was correlated to stock distribution we compared three metrics describing features of the distributions (the mean distance to the coast, the total area of distribution, and a clustering index) for concomitant acoustic survey observations and fishing set positions identified from VMS. For two of these metrics (mean distance to the coast and clustering index), fishing and survey data were significantly correlated. We conclude that the location of purse-seine fishing sets yields significant and valuable information on the distribution of the Peruvian anchovy stock and ultimately on its vulnerability to the fishery. For example, a high concentration of sets in the near coastal zone could potentially be used as a warning signal of high levels of stock vulnerability and trigger appropriate management measures aimed at reducing fishing effort.
Milles, Julien; Zhu, Yue Min; Gimenez, Gérard; Guttmann, Charles R G; Magnin, Isabelle E
2007-03-01
A novel approach for correcting intensity nonuniformity in magnetic resonance imaging (MRI) is presented. This approach is based on the simultaneous use of spatial and gray-level histogram information. Spatial information about intensity nonuniformity is obtained using cubic B-spline smoothing. Gray-level histogram information of the image corrupted by intensity nonuniformity is exploited from a frequential point of view. The proposed correction method is illustrated using both physical phantom and human brain images. The results are consistent with theoretical prediction, and demonstrate a new way of dealing with intensity nonuniformity problems. They are all the more significant as the ground truth on intensity nonuniformity is unknown in clinical images.
Correction of mid-spatial-frequency errors by smoothing in spin motion for CCOS
NASA Astrophysics Data System (ADS)
Zhang, Yizhong; Wei, Chaoyang; Shao, Jianda; Xu, Xueke; Liu, Shijie; Hu, Chen; Zhang, Haichao; Gu, Haojin
2015-08-01
Smoothing is a convenient and efficient way to correct mid-spatial-frequency errors. Quantifying the smoothing effect allows improvements in efficiency for finishing precision optics. A series experiments in spin motion are performed to study the smoothing effects about correcting mid-spatial-frequency errors. Some of them use a same pitch tool at different spinning speed, and others at a same spinning speed with different tools. Introduced and improved Shu's model to describe and compare the smoothing efficiency with different spinning speed and different tools. From the experimental results, the mid-spatial-frequency errors on the initial surface were nearly smoothed out after the process in spin motion and the number of smoothing times can be estimated by the model before the process. Meanwhile this method was also applied to smooth the aspherical component, which has an obvious mid-spatial-frequency error after Magnetorheological Finishing processing. As a result, a high precision aspheric optical component was obtained with PV=0.1λ and RMS=0.01λ.
Ahlgren, André; Wirestam, Ronnie; Petersen, Esben Thade; Ståhlberg, Freddy; Knutsson, Linda
2014-09-01
Quantitative perfusion MRI based on arterial spin labeling (ASL) is hampered by partial volume effects (PVEs), arising due to voxel signal cross-contamination between different compartments. To address this issue, several partial volume correction (PVC) methods have been presented. Most previous methods rely on segmentation of a high-resolution T1 -weighted morphological image volume that is coregistered to the low-resolution ASL data, making the result sensitive to errors in the segmentation and coregistration. In this work, we present a methodology for partial volume estimation and correction, using only low-resolution ASL data acquired with the QUASAR sequence. The methodology consists of a T1 -based segmentation method, with no spatial priors, and a modified PVC method based on linear regression. The presented approach thus avoids prior assumptions about the spatial distribution of brain compartments, while also avoiding coregistration between different image volumes. Simulations based on a digital phantom as well as in vivo measurements in 10 volunteers were used to assess the performance of the proposed segmentation approach. The simulation results indicated that QUASAR data can be used for robust partial volume estimation, and this was confirmed by the in vivo experiments. The proposed PVC method yielded probable perfusion maps, comparable to a reference method based on segmentation of a high-resolution morphological scan. Corrected gray matter (GM) perfusion was 47% higher than uncorrected values, suggesting a significant amount of PVEs in the data. Whereas the reference method failed to completely eliminate the dependence of perfusion estimates on the volume fraction, the novel approach produced GM perfusion values independent of GM volume fraction. The intra-subject coefficient of variation of corrected perfusion values was lowest for the proposed PVC method. As shown in this work, low-resolution partial volume estimation in connection with ASL perfusion estimation is feasible, and provides a promising tool for decoupling perfusion and tissue volume. Copyright © 2014 John Wiley & Sons, Ltd.
Spatially coupled low-density parity-check error correction for holographic data storage
NASA Astrophysics Data System (ADS)
Ishii, Norihiko; Katano, Yutaro; Muroi, Tetsuhiko; Kinoshita, Nobuhiro
2017-09-01
The spatially coupled low-density parity-check (SC-LDPC) was considered for holographic data storage. The superiority of SC-LDPC was studied by simulation. The simulations show that the performance of SC-LDPC depends on the lifting number, and when the lifting number is over 100, SC-LDPC shows better error correctability compared with irregular LDPC. SC-LDPC is applied to the 5:9 modulation code, which is one of the differential codes. The error-free point is near 2.8 dB and over 10-1 can be corrected in simulation. From these simulation results, this error correction code can be applied to actual holographic data storage test equipment. Results showed that 8 × 10-2 can be corrected, furthermore it works effectively and shows good error correctability.
The Role of Diffusion in the Transport of Energetic Electrons during Solar Flares
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bian, Nicolas H.; Kontar, Eduard P.; Emslie, A. Gordon, E-mail: nicolas.bian@glasgow.gla.ac.uk, E-mail: emslieg@wku.edu
2017-02-01
The transport of the energy contained in suprathermal electrons in solar flares plays a key role in our understanding of many aspects of flare physics, from the spatial distributions of hard X-ray emission and energy deposition in the ambient atmosphere to global energetics. Historically the transport of these particles has been largely treated through a deterministic approach, in which first-order secular energy loss to electrons in the ambient target is treated as the dominant effect, with second-order diffusive terms (in both energy and angle) generally being either treated as a small correction or even neglected. Here, we critically analyze thismore » approach, and we show that spatial diffusion through pitch-angle scattering necessarily plays a very significant role in the transport of electrons. We further show that a satisfactory treatment of the diffusion process requires consideration of non-local effects, so that the electron flux depends not just on the local gradient of the electron distribution function but on the value of this gradient within an extended region encompassing a significant fraction of a mean free path. Our analysis applies generally to pitch-angle scattering by a variety of mechanisms, from Coulomb collisions to turbulent scattering. We further show that the spatial transport of electrons along the magnetic field of a flaring loop can be modeled rather effectively as a Continuous Time Random Walk with velocity-dependent probability distribution functions of jump sizes and occurrences, both of which can be expressed in terms of the scattering mean free path.« less
NASA Astrophysics Data System (ADS)
Lu, Bing; He, Yuhong
2017-06-01
Investigating spatio-temporal variations of species composition in grassland is an essential step in evaluating grassland health conditions, understanding the evolutionary processes of the local ecosystem, and developing grassland management strategies. Space-borne remote sensing images (e.g., MODIS, Landsat, and Quickbird) with spatial resolutions varying from less than 1 m to 500 m have been widely applied for vegetation species classification at spatial scales from community to regional levels. However, the spatial resolutions of these images are not fine enough to investigate grassland species composition, since grass species are generally small in size and highly mixed, and vegetation cover is greatly heterogeneous. Unmanned Aerial Vehicle (UAV) as an emerging remote sensing platform offers a unique ability to acquire imagery at very high spatial resolution (centimetres). Compared to satellites or airplanes, UAVs can be deployed quickly and repeatedly, and are less limited by weather conditions, facilitating advantageous temporal studies. In this study, we utilize an octocopter, on which we mounted a modified digital camera (with near-infrared (NIR), green, and blue bands), to investigate species composition in a tall grassland in Ontario, Canada. Seven flight missions were conducted during the growing season (April to December) in 2015 to detect seasonal variations, and four of them were selected in this study to investigate the spatio-temporal variations of species composition. To quantitatively compare images acquired at different times, we establish a processing flow of UAV-acquired imagery, focusing on imagery quality evaluation and radiometric correction. The corrected imagery is then applied to an object-based species classification. Maps of species distribution are subsequently used for a spatio-temporal change analysis. Results indicate that UAV-acquired imagery is an incomparable data source for studying fine-scale grassland species composition, owing to its high spatial resolution. The overall accuracy is around 85% for images acquired at different times. Species composition is spatially attributed by topographical features and soil moisture conditions. Spatio-temporal variation of species composition implies the growing process and succession of different species, which is critical for understanding the evolutionary features of grassland ecosystems. Strengths and challenges of applying UAV-acquired imagery for vegetation studies are summarized at the end.
Hyperspectral remote sensing of wild oyster reefs
NASA Astrophysics Data System (ADS)
Le Bris, Anthony; Rosa, Philippe; Lerouxel, Astrid; Cognie, Bruno; Gernez, Pierre; Launeau, Patrick; Robin, Marc; Barillé, Laurent
2016-04-01
The invasion of the wild oyster Crassostrea gigas along the western European Atlantic coast has generated changes in the structure and functioning of intertidal ecosystems. Considered as an invasive species and a trophic competitor of the cultivated conspecific oyster, it is now seen as a resource by oyster farmers following recurrent mass summer mortalities of oyster spat since 2008. Spatial distribution maps of wild oyster reefs are required by local authorities to help define management strategies. In this work, visible-near infrared (VNIR) hyperspectral and multispectral remote sensing was investigated to map two contrasted intertidal reef structures: clusters of vertical oysters building three-dimensional dense reefs in muddy areas and oysters growing horizontally creating large flat reefs in rocky areas. A spectral library, collected in situ for various conditions with an ASD spectroradiometer, was used to run Spectral Angle Mapper classifications on airborne data obtained with an HySpex sensor (160 spectral bands) and SPOT satellite HRG multispectral data (3 spectral bands). With HySpex spectral/spatial resolution, horizontal oysters in the rocky area were correctly classified but the detection was less efficient for vertical oysters in muddy areas. Poor results were obtained with the multispectral image and from spatially or spectrally degraded HySpex data, it was clear that the spectral resolution was more important than the spatial resolution. In fact, there was a systematic mud deposition on shells of vertical oyster reefs explaining the misclassification of 30% of pixels recognized as mud or microphytobenthos. Spatial distribution maps of oyster reefs were coupled with in situ biomass measurements to illustrate the interest of a remote sensing product to provide stock estimations of wild oyster reefs to be exploited by oyster producers. This work highlights the interest of developing remote sensing techniques for aquaculture applications in coastal areas.
Balanced Cortical Microcircuitry for Spatial Working Memory Based on Corrective Feedback Control
2014-01-01
A hallmark of working memory is the ability to maintain graded representations of both the spatial location and amplitude of a memorized stimulus. Previous work has identified a neural correlate of spatial working memory in the persistent maintenance of spatially specific patterns of neural activity. How such activity is maintained by neocortical circuits remains unknown. Traditional models of working memory maintain analog representations of either the spatial location or the amplitude of a stimulus, but not both. Furthermore, although most previous models require local excitation and lateral inhibition to maintain spatially localized persistent activity stably, the substrate for lateral inhibitory feedback pathways is unclear. Here, we suggest an alternative model for spatial working memory that is capable of maintaining analog representations of both the spatial location and amplitude of a stimulus, and that does not rely on long-range feedback inhibition. The model consists of a functionally columnar network of recurrently connected excitatory and inhibitory neural populations. When excitation and inhibition are balanced in strength but offset in time, drifts in activity trigger spatially specific negative feedback that corrects memory decay. The resulting networks can temporally integrate inputs at any spatial location, are robust against many commonly considered perturbations in network parameters, and, when implemented in a spiking model, generate irregular neural firing characteristic of that observed experimentally during persistent activity. This work suggests balanced excitatory–inhibitory memory circuits implementing corrective negative feedback as a substrate for spatial working memory. PMID:24828633
NASA Astrophysics Data System (ADS)
Curreli, Matteo; Corona, Roberto; Montaldo, Nicola; Albertson, John D.; Oren, Ram
2014-05-01
Mediterranean ecosystems are characterized by a strong heterogeneity, and often by water-limited conditions. In these conditions contrasting plant functional types (PFT, e.g. grass and woody vegetation) compete for the water use. Both the vegetation cover spatial distribution and the soil properties impact the soil moisture (SM) spatial distribution. Indeed, vegetation cover density and type affects evapotranspiration (ET), which is the main lack of the soil water balance in these ecosystems. With the objective to carefully estimate SM and ET spatial distribution in a Mediterranean water-limited ecosystem and understanding SM and ET relationships, an extended field campaign is carried out. The study was performed in a heterogeneous ecosystem in Orroli, Sardinia (Italy). The experimental site is a typical Mediterranean ecosystem where the vegetation is distributed in patches of woody vegetation (wild olives mainly) and grass. Soil depth is low and spatially varies between 10 cm and 40 cm, without any correlation with the vegetation spatial distribution. ET, land-surface fluxes and CO2 fluxes are estimated by an eddy covariance technique based micrometeorological tower. But in heterogeneous ecosystems a key assumption of the eddy covariance theory, the homogeneity of the surface, is not preserved and the ET estimate may be not correct. Hence, we estimate ET of the woody vegetation using the thermal dissipation method (i.e. sap flow technique) for comparing the two methodologies. Due the high heterogeneity of the vegetation and soil properties of the field a total of 54 sap flux sensors were installed. 14 clumps of wild olives within the eddy covariance footprint were identified as the most representative source of flux and they were instrumented with the thermal dissipation probes. Measurements of diameter at the height of sensor installation (height of 0.4 m above ground) were recorded in all the clumps. Bark thickness and sapwood depth were measured on several trees to obtain a generalized estimates of sapwood depth. The known of allometric relationships between sapwood area, diameter and canopy cover area within the eddy covariance footprint helped for the application of a reliable scaling procedure of the local sap flow estimates which are in a good agreement with the estimates of ET eddy covariance based. Soil moisture were also extensively monitored through 25 probes installed in the eddy covariance footprint. Results show that comparing eddy covariance and sap flow ET estimates eddy covariance technique is still accurate in this heterogeneous field, whereas the key assumption, surface homogeneity, is not preserved. Furthermore, interestingly wild olives still transpire at higher rates for the driest soil moisture conditions, confirming the hydraulic redistribution from soil below the roots, and from roots penetrating deep cracks in the underlying basalt parent rock.
Spatial heterogeneity of leaf area index across scales from simulation and remote sensing
NASA Astrophysics Data System (ADS)
Reichenau, Tim G.; Korres, Wolfgang; Montzka, Carsten; Schneider, Karl
2016-04-01
Leaf area index (LAI, single sided leaf area per ground area) influences mass and energy exchange of vegetated surfaces. Therefore LAI is an input variable for many land surface schemes of coupled large scale models, which do not simulate LAI. Since these models typically run on rather coarse resolution grids, LAI is often inferred from coarse resolution remote sensing. However, especially in agriculturally used areas, a grid cell of these products often covers more than a single land-use. In that case, the given LAI does not apply to any single land-use. Therefore, the overall spatial heterogeneity in these datasets differs from that on resolutions high enough to distinguish areas with differing land-use. Detailed process-based plant growth models simulate LAI for separate plant functional types or specific species. However, limited availability of observations causes reduced spatial heterogeneity of model input data (soil, weather, land-use). Since LAI is strongly heterogeneous in space and time and since processes depend on LAI in a nonlinear way, a correct representation of LAI spatial heterogeneity is also desirable on coarse resolutions. The current study assesses this issue by comparing the spatial heterogeneity of LAI from remote sensing (RapidEye) and process-based simulations (DANUBIA simulation system) across scales. Spatial heterogeneity is assessed by analyzing LAI frequency distributions (spatial variability) and semivariograms (spatial structure). Test case is the arable land in the fertile loess plain of the Rur catchment near the Germany-Netherlands border.
Ding, Yi; Peng, Kai; Yu, Miao; Lu, Lei; Zhao, Kun
2017-08-01
The performance of the two selected spatial frequency phase unwrapping methods is limited by a phase error bound beyond which errors will occur in the fringe order leading to a significant error in the recovered absolute phase map. In this paper, we propose a method to detect and correct the wrong fringe orders. Two constraints are introduced during the fringe order determination of two selected spatial frequency phase unwrapping methods. A strategy to detect and correct the wrong fringe orders is also described. Compared with the existing methods, we do not need to estimate the threshold associated with absolute phase values to determine the fringe order error, thus making it more reliable and avoiding the procedure of search in detecting and correcting successive fringe order errors. The effectiveness of the proposed method is validated by the experimental results.
NASA Astrophysics Data System (ADS)
Murray, K. D.; Lohman, R.
2017-12-01
Areas of large-scale subsidence are observed over much of the San Joaquin Valley of California due to the extraction of groundwater and hydrocarbons from the subsurface.These signals span regions with spatial extents of up to 100 km and have rates of up to 45 cm/yr or more. InSAR and GPS are complementary methods commonly used to measure such ground displacements and can provide important constraints on crustal deformation models, support groundwater studies, and inform water resource management efforts. However, current standard methods for processing these data sets and creating displacement time series are suboptimal for the deformation observed in areas like the San Joaquin Valley because (1) the ground surface properties are constantly changing due largely to agricultural activity, resulting in low coherence in half or more of a SAR frame, and (2) the deformation signals are distributed throughout the SAR frames, and are comparable to the size of the frames themselves. Therefore, referencing areas of deformation to non-deforming areas and correcting for long wavelength signals (e.g. atmospheric delays, orbital errors) is particularly difficult. We address these challenges by exploiting pixels that are stable in space and time, and use them for weighted spatial averaging and selective filtering before unwrapping. We then compare a range of methods for both long wavelength corrections and referencing via automatic partitioning of non-deforming areas, then benchmark results against continuous GPS measurements. Our final time series consist of nearly 15 years of displacement measurements from continuous GPS data, and Envisat, ALOS-1, Sentinel SAR data, and show significant temporal and spatial variations. We find that the choice of reference and long wavelength corrections can significantly bias long-term rate and seasonal amplitude estimates, causing variations of as much as 100% of the mean estimate. As we enter an era with free and open data access and regular observations plans from missions such as NISAR and the Sentinel constellation, our approach will help users evaluate the significance of observed deformation at a range of spatial scales and in areas with challenging surface properties.
Head-mounted spatial instruments II: Synthetic reality or impossible dream
NASA Technical Reports Server (NTRS)
Ellis, Stephen R.; Grunwald, Arthur
1989-01-01
A spatial instrument is defined as a spatial display which has been either geometrically or symbolically enhanced to enable a user to accomplish a particular task. Research conducted over the past several years on 3-D spatial instruments has shown that perspective displays, even when viewed from the correct viewpoint, are subject to systematic viewer biases. These biases interfere with correct spatial judgements of the presented pictorial information. The design of spatial instruments may not only require the introduction of compensatory distortions to remove the naturally occurring biases but also may significantly benefit from the introduction of artificial distortions which enhance performance. However, these image manipulations can cause a loss of visual-vestibular coordination and induce motion sickness. Consequently, the design of head-mounted spatial instruments will require an understanding of the tolerable limits of visual-vestibular discord.
NASA Technical Reports Server (NTRS)
Bromwich, David H.; Chen, Qiu-shi
2002-01-01
Observations of precipitation over Greenland are limited. Direct precipitation measurements for the whole ice sheet are impractical, and those in the coastal region have substantial uncertainty but may be correctable with some effort. However, the analyzed wind, geopotential height and moisture fields are available for recent years, and the precipitation is retrievable from these fields by a dynamic method. Based on recent Greenland precipitation from dynamic studies, several deficiencies in the precipitation spatial distributions from these dynamic methods were evaluated by Bromwich et al.
Mauritzen, Mette; Derocher, Andrew E.; Wiig, Øystein; Belikov, Stanislav; Boltunov, Andrei N.; Garner, Gerald W.
2002-01-01
1. Animal populations, defined by geographical areas within a species’ distribution where population dynamics are largely regulated by births and deaths rather than by migration from surrounding areas, may be the correct unit for wildlife management. However, in heterogeneous landscapes varying habitat quality may yield subpopulations with distinct patterns in resource use and demography significant to the dynamics of populations.2. To define the spatial population structure of polar bears Ursus maritimus in the Norwegian and western Russian Arctic, and to assess the existence of a shared population between the two countries, we analysed satellite telemetry data obtained from 105 female polar bears over 12 years.3. Using both cluster analyses and home-range estimation methods, we identified five population units inhabiting areas with different sea-ice characteristics and prey availability.4. The continuous distribution of polar bear positions indicated that the different subpopulations formed one continuous polar bear population in the Norwegian and western Russian Arctic. Hence, Norway and Russia have a shared management responsibility.5. The spatial population structure identified will provide a guide for evaluating geographical patterns in polar bear ecology, the dynamics of polar bear–seal relationships and the effects of habitat alteration due to climate change. The work illustrates the importance of defining population borders and subpopulation structure in understanding the dynamics and management of larger animals.
Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin
Shrestha, M.S.; Artan, G.A.; Bajracharya, S.R.; Gautam, D.K.; Tokar, S.A.
2011-01-01
In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32000km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC-RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC-RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC-RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction. ?? 2011 The Authors. Journal of Flood Risk Management ?? 2011 The Chartered Institution of Water and Environmental Management.
Bias-adjusted satellite-based rainfall estimates for predicting floods: Narayani Basin
Artan, Guleid A.; Tokar, S.A.; Gautam, D.K.; Bajracharya, S.R.; Shrestha, M.S.
2011-01-01
In Nepal, as the spatial distribution of rain gauges is not sufficient to provide detailed perspective on the highly varied spatial nature of rainfall, satellite-based rainfall estimates provides the opportunity for timely estimation. This paper presents the flood prediction of Narayani Basin at the Devghat hydrometric station (32 000 km2) using bias-adjusted satellite rainfall estimates and the Geospatial Stream Flow Model (GeoSFM), a spatially distributed, physically based hydrologic model. The GeoSFM with gridded gauge observed rainfall inputs using kriging interpolation from 2003 was used for calibration and 2004 for validation to simulate stream flow with both having a Nash Sutcliff Efficiency of above 0.7. With the National Oceanic and Atmospheric Administration Climate Prediction Centre's rainfall estimates (CPC_RFE2.0), using the same calibrated parameters, for 2003 the model performance deteriorated but improved after recalibration with CPC_RFE2.0 indicating the need to recalibrate the model with satellite-based rainfall estimates. Adjusting the CPC_RFE2.0 by a seasonal, monthly and 7-day moving average ratio, improvement in model performance was achieved. Furthermore, a new gauge-satellite merged rainfall estimates obtained from ingestion of local rain gauge data resulted in significant improvement in flood predictability. The results indicate the applicability of satellite-based rainfall estimates in flood prediction with appropriate bias correction.
Toward transient finite element simulation of thermal deformation of machine tools in real-time
NASA Astrophysics Data System (ADS)
Naumann, Andreas; Ruprecht, Daniel; Wensch, Joerg
2018-01-01
Finite element models without simplifying assumptions can accurately describe the spatial and temporal distribution of heat in machine tools as well as the resulting deformation. In principle, this allows to correct for displacements of the Tool Centre Point and enables high precision manufacturing. However, the computational cost of FE models and restriction to generic algorithms in commercial tools like ANSYS prevents their operational use since simulations have to run faster than real-time. For the case where heat diffusion is slow compared to machine movement, we introduce a tailored implicit-explicit multi-rate time stepping method of higher order based on spectral deferred corrections. Using the open-source FEM library DUNE, we show that fully coupled simulations of the temperature field are possible in real-time for a machine consisting of a stock sliding up and down on rails attached to a stand.
Respiratory motion correction in emission tomography image reconstruction.
Reyes, Mauricio; Malandain, Grégoire; Koulibaly, Pierre Malick; González Ballester, Miguel A; Darcourt, Jacques
2005-01-01
In Emission Tomography imaging, respiratory motion causes artifacts in lungs and cardiac reconstructed images, which lead to misinterpretations and imprecise diagnosis. Solutions like respiratory gating, correlated dynamic PET techniques, list-mode data based techniques and others have been tested with improvements over the spatial activity distribution in lungs lesions, but with the disadvantages of requiring additional instrumentation or discarding part of the projection data used for reconstruction. The objective of this study is to incorporate respiratory motion correction directly into the image reconstruction process, without any additional acquisition protocol consideration. To this end, we propose an extension to the Maximum Likelihood Expectation Maximization (MLEM) algorithm that includes a respiratory motion model, which takes into account the displacements and volume deformations produced by the respiratory motion during the data acquisition process. We present results from synthetic simulations incorporating real respiratory motion as well as from phantom and patient data.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Liu, Yuxuan; Martin, William; Williams, Mark
In this paper, a correction-based resonance self-shielding method is developed that allows annular subdivision of the fuel rod. The method performs the conventional iteration of the embedded self-shielding method (ESSM) without subdivision of the fuel to capture the interpin shielding effect. The resultant self-shielded cross sections are modified by correction factors incorporating the intrapin effects of radial variation of the shielded cross section, radial temperature distribution, and resonance interference. A quasi–one-dimensional slowing-down equation is developed to calculate such correction factors. The method is implemented in the DeCART code and compared with the conventional ESSM and subgroup method with benchmark MCNPmore » results. The new method yields substantially improved results for both spatially dependent reaction rates and eigenvalues for typical pressurized water reactor pin cell cases with uniform and nonuniform fuel temperature profiles. Finally, the new method is also proved effective in treating assembly heterogeneity and complex material composition such as mixed oxide fuel, where resonance interference is much more intense.« less
NASA Astrophysics Data System (ADS)
Zhang, Huifang; Yang, Minghong; Xu, Xueke; Wu, Lunzhe; Yang, Weiguang; Shao, Jianda
2017-10-01
The surface figure control of the conventional annular polishing system is realized ordinarily by the interaction between the conditioner and the lap. The surface profile of the pitch lap corrected by the marble conditioner has been measured and analyzed as a function of kinematics, loading conditions, and polishing time. The surface profile measuring equipment of the large lap based on laser alignment was developed with the accuracy of about 1μm. The conditioning mechanism of the conditioner is simply determined by the kinematics and fully fitting principle, but the unexpected surface profile deviation of the lap emerged frequently due to numerous influencing factors including the geometrical relationship, the pressure distribution at the conditioner/lap interface. Both factors are quantitatively evaluated and described, and have been combined to develop a spatial and temporal model to simulate the surface profile evolution of pitch lap. The simulations are consistent with the experiments. This study is an important step toward deterministic full-aperture annular polishing, providing a beneficial guidance for the surface profile correction of the pitch lap.
Cortico-muscular coherence on artifact corrected EEG-EMG data recorded with a MRI scanner.
Muthuraman, M; Galka, A; Hong, V N; Heute, U; Deuschl, G; Raethjen, J
2013-01-01
Simultaneous recording of electroencephalogram (EEG) and electromyogram (EMG) with magnetic resonance imaging (MRI) provides great potential for studying human brain activity with high temporal and spatial resolution. But, due to the MRI, the recorded signals are contaminated with artifacts. The correction of these artifacts is important to use these signals for further spectral analysis. The coherence can reveal the cortical representation of peripheral muscle signal in particular motor tasks, e.g. finger movements. The artifact correction of these signals was done by two different algorithms the Brain vision analyzer (BVA) and the Matlab FMRIB plug-in for EEGLAB. The Welch periodogram method was used for estimating the cortico-muscular coherence. Our analysis revealed coherence with a frequency of 5Hz in the contralateral side of the brain. The entropy is estimated for the calculated coherence to get the distribution of coherence in the scalp. The significance of the paper is to identify the optimal algorithm to rectify the MR artifacts and as a first step to use both these signals EEG and EMG in conjunction with MRI for further studies.
NASA Astrophysics Data System (ADS)
Maloney, Chris; Lormeau, Jean Pierre; Dumas, Paul
2016-07-01
Many astronomical sensing applications operate in low-light conditions; for these applications every photon counts. Controlling mid-spatial frequencies and surface roughness on astronomical optics are critical for mitigating scattering effects such as flare and energy loss. By improving these two frequency regimes higher contrast images can be collected with improved efficiency. Classically, Magnetorheological Finishing (MRF) has offered an optical fabrication technique to correct low order errors as well has quilting/print-through errors left over in light-weighted optics from conventional polishing techniques. MRF is a deterministic, sub-aperture polishing process that has been used to improve figure on an ever expanding assortment of optical geometries, such as planos, spheres, on and off axis aspheres, primary mirrors and freeform optics. Precision optics are routinely manufactured by this technology with sizes ranging from 5-2,000mm in diameter. MRF can be used for form corrections; turning a sphere into an asphere or free form, but more commonly for figure corrections achieving figure errors as low as 1nm RMS while using careful metrology setups. Recent advancements in MRF technology have improved the polishing performance expected for astronomical optics in low, mid and high spatial frequency regimes. Deterministic figure correction with MRF is compatible with most materials, including some recent examples on Silicon Carbide and RSA905 Aluminum. MRF also has the ability to produce `perfectly-bad' compensating surfaces, which may be used to compensate for measured or modeled optical deformation from sources such as gravity or mounting. In addition, recent advances in MRF technology allow for corrections of mid-spatial wavelengths as small as 1mm simultaneously with form error correction. Efficient midspatial frequency corrections make use of optimized process conditions including raster polishing in combination with a small tool size. Furthermore, a novel MRF fluid, called C30, has been developed to finish surfaces to ultra-low roughness (ULR) and has been used as the low removal rate fluid required for fine figure correction of mid-spatial frequency errors. This novel MRF fluid is able to achieve <4Å RMS on Nickel-plated Aluminum and even <1.5Å RMS roughness on Silicon, Fused Silica and other materials. C30 fluid is best utilized within a fine figure correction process to target mid-spatial frequency errors as well as smooth surface roughness 'for free' all in one step. In this paper we will discuss recent advancements in MRF technology and the ability to meet requirements for precision optics in low, mid and high spatial frequency regimes and how improved MRF performance addresses the need for achieving tight specifications required for astronomical optics.
NASA Astrophysics Data System (ADS)
Coene, A.; Crevecoeur, G.; Dupré, L.; Vaes, P.
2013-06-01
In recent years, magnetic nanoparticles (MNPs) have gained increased attention due to their superparamagnetic properties. These properties allow the development of innovative biomedical applications such as targeted drug delivery and tumour heating. However, these modalities lack effective operation arising from the inaccurate quantification of the spatial MNP distribution. This paper proposes an approach for assessing the one-dimensional (1D) MNP distribution using electron paramagnetic resonance (EPR). EPR is able to accurately determine the MNP concentration in a single volume but not the MNP distribution throughout this volume. A new approach that exploits the solution of inverse problems for the correct interpretation of the measured EPR signals, is investigated. We achieve reconstruction of the 1D distribution of MNPs using EPR. Furthermore, the impact of temperature control on the reconstructed distributions is analysed by comparing two EPR setups where the latter setup is temperature controlled. Reconstruction quality for the temperature-controlled setup increases with an average of 5% and with a maximum increase of 13% for distributions with relatively lower iron concentrations and higher resolutions. However, these measurements are only a validation of our new method and form no hard limits.
Detecting and removing multiplicative spatial bias in high-throughput screening technologies.
Caraus, Iurie; Mazoure, Bogdan; Nadon, Robert; Makarenkov, Vladimir
2017-10-15
Considerable attention has been paid recently to improve data quality in high-throughput screening (HTS) and high-content screening (HCS) technologies widely used in drug development and chemical toxicity research. However, several environmentally- and procedurally-induced spatial biases in experimental HTS and HCS screens decrease measurement accuracy, leading to increased numbers of false positives and false negatives in hit selection. Although effective bias correction methods and software have been developed over the past decades, almost all of these tools have been designed to reduce the effect of additive bias only. Here, we address the case of multiplicative spatial bias. We introduce three new statistical methods meant to reduce multiplicative spatial bias in screening technologies. We assess the performance of the methods with synthetic and real data affected by multiplicative spatial bias, including comparisons with current bias correction methods. We also describe a wider data correction protocol that integrates methods for removing both assay and plate-specific spatial biases, which can be either additive or multiplicative. The methods for removing multiplicative spatial bias and the data correction protocol are effective in detecting and cleaning experimental data generated by screening technologies. As our protocol is of a general nature, it can be used by researchers analyzing current or next-generation high-throughput screens. The AssayCorrector program, implemented in R, is available on CRAN. makarenkov.vladimir@uqam.ca. Supplementary data are available at Bioinformatics online. © The Author (2017). Published by Oxford University Press. All rights reserved. For Permissions, please email: journals.permissions@oup.com
Methodological challenges to bridge the gap between regional climate and hydrology models
NASA Astrophysics Data System (ADS)
Bozhinova, Denica; José Gómez-Navarro, Juan; Raible, Christoph; Felder, Guido
2017-04-01
The frequency and severity of floods worldwide, together with their impacts, are expected to increase under climate change scenarios. It is therefore very important to gain insight into the physical mechanisms responsible for such events in order to constrain the associated uncertainties. Model simulations of the climate and hydrological processes are important tools that can provide insight in the underlying physical processes and thus enable an accurate assessment of the risks. Coupled together, they can provide a physically consistent picture that allows to assess the phenomenon in a comprehensive way. However, climate and hydrological models work at different temporal and spatial scales, so there are a number of methodological challenges that need to be carefully addressed. An important issue pertains the presence of biases in the simulation of precipitation. Climate models in general, and Regional Climate models (RCMs) in particular, are affected by a number of systematic biases that limit their reliability. In many studies, prominently the assessment of changes due to climate change, such biases are minimised by applying the so-called delta approach, which focuses on changes disregarding absolute values that are more affected by biases. However, this approach is not suitable in this scenario, as the absolute value of precipitation, rather than the change, is fed into the hydrological model. Therefore, bias has to be previously removed, being this a complex matter where various methodologies have been proposed. In this study, we apply and discuss the advantages and caveats of two different methodologies that correct the simulated precipitation to minimise differences with respect an observational dataset: a linear fit (FIT) of the accumulated distributions and Quantile Mapping (QM). The target region is Switzerland, and therefore the observational dataset is provided by MeteoSwiss. The RCM is the Weather Research and Forecasting model (WRF), driven at the boundaries by the Community Earth System Model (CESM). The raw simulation driven by CESM exhibit prominent biases that stand out in the evolution of the annual cycle and demonstrate that the correction of biases is mandatory in this type of studies, rather than a minor correction that might be neglected. The simulation spans the period 1976 - 2005, although the application of the correction is carried out on a daily basis. Both methods lead to a corrected field of precipitation that respects the temporal evolution of the simulated precipitation, at the same time that mimics the distribution of precipitation according to the one in the observations. Due to the nature of the two methodologies, there are important differences between the products of both corrections, that lead to dataset with different properties. FIT is generally more accurate regarding the reproduction of the tails of the distribution, i.e. extreme events, whereas the nature of QM renders it a general-purpose correction whose skill is equally distributed across the full distribution of precipitation, including central values.
Projected changes in the evolution of drought assessed with the SPEI over the Czech Republic
NASA Astrophysics Data System (ADS)
Potop, V.; Boroneana, C.; Stepanek, P.; Skalak, P.; Mozny, M.
2012-04-01
In previous studies the spatial and temporal evolution of drought events in the Czech Republic were extensively analyzed by comparing results from the most advanced drought indices (e.g. the SPI and SPEI), which take into account the role of antecedent conditions in quantifying drought severity. In the present study, the Standardized Precipitation Evapotranspiration Index (SPEI) was adopted to assess and project drought characteristics in the Czech Republic based on the regional climate model ALADIN-Climate/CZ simulated data. The simulations were conducted at high resolution (10km) for the current (1961-2000) and two future climates (2021-2050 and 2071-2100). First, the observed data of air temperature and precipitation totals was transferred into a regular grid of ALADIN-Climate/CZ model. The bias correction was applied on the scenario runs. The bias correction method is based on variable correction using individual percentiles whose relationship is derived from observations and control RCM simulation. The SPEI was calculated based on observed monthly data of mean temperature and precipitation totals for the period 1961-1990, as reference period, and for the periods 2021-2050 and 2071-2100, as future climates under A1B SRES scenario. The SPEI were calculated with various lags, 1, 3, 6, 12 and 24 months because the drought at these time scales is relevant for agricultural, hydrological and socio-economic impact, respectively. The study refers at the warm season of the year (April to September). As in the case of observational study, we have identified three climatically homogeneous regions, corresponding to the altitudes below 400 m, between 401 and 700 m and, above 700 m. For these three regions the frequency distribution of the SPEI values in 7 classes of drought category (%) were calculated based on grid point data falling in each region, both for the observed data and scenario runs. The paper presents the projected changes in frequency distribution of SPEI at various time scales, in intensity, duration and spatial distribution of drought over the territory of the Czech Republic under A1B scenario for the middle and the end of 21st century. We gratefully acknowledge the support of the Ministry of Education, Youth and Sports for projects OC10010.
Zarco-Perello, Salvador; Simões, Nuno
2017-01-01
Information about the distribution and abundance of the habitat-forming sessile organisms in marine ecosystems is of great importance for conservation and natural resource managers. Spatial interpolation methodologies can be useful to generate this information from in situ sampling points, especially in circumstances where remote sensing methodologies cannot be applied due to small-scale spatial variability of the natural communities and low light penetration in the water column. Interpolation methods are widely used in environmental sciences; however, published studies using these methodologies in coral reef science are scarce. We compared the accuracy of the two most commonly used interpolation methods in all disciplines, inverse distance weighting (IDW) and ordinary kriging (OK), to predict the distribution and abundance of hard corals, octocorals, macroalgae, sponges and zoantharians and identify hotspots of these habitat-forming organisms using data sampled at three different spatial scales (5, 10 and 20 m) in Madagascar reef, Gulf of Mexico. The deeper sandy environments of the leeward and windward regions of Madagascar reef were dominated by macroalgae and seconded by octocorals. However, the shallow rocky environments of the reef crest had the highest richness of habitat-forming groups of organisms; here, we registered high abundances of octocorals and macroalgae, with sponges, Millepora alcicornis and zoantharians dominating in some patches, creating high levels of habitat heterogeneity. IDW and OK generated similar maps of distribution for all the taxa; however, cross-validation tests showed that IDW outperformed OK in the prediction of their abundances. When the sampling distance was at 20 m, both interpolation techniques performed poorly, but as the sampling was done at shorter distances prediction accuracies increased, especially for IDW. OK had higher mean prediction errors and failed to correctly interpolate the highest abundance values measured in situ , except for macroalgae, whereas IDW had lower mean prediction errors and high correlations between predicted and measured values in all cases when sampling was every 5 m. The accurate spatial interpolations created using IDW allowed us to see the spatial variability of each taxa at a biological and spatial resolution that remote sensing would not have been able to produce. Our study sets the basis for further research projects and conservation management in Madagascar reef and encourages similar studies in the region and other parts of the world where remote sensing technologies are not suitable for use.
Simões, Nuno
2017-01-01
Information about the distribution and abundance of the habitat-forming sessile organisms in marine ecosystems is of great importance for conservation and natural resource managers. Spatial interpolation methodologies can be useful to generate this information from in situ sampling points, especially in circumstances where remote sensing methodologies cannot be applied due to small-scale spatial variability of the natural communities and low light penetration in the water column. Interpolation methods are widely used in environmental sciences; however, published studies using these methodologies in coral reef science are scarce. We compared the accuracy of the two most commonly used interpolation methods in all disciplines, inverse distance weighting (IDW) and ordinary kriging (OK), to predict the distribution and abundance of hard corals, octocorals, macroalgae, sponges and zoantharians and identify hotspots of these habitat-forming organisms using data sampled at three different spatial scales (5, 10 and 20 m) in Madagascar reef, Gulf of Mexico. The deeper sandy environments of the leeward and windward regions of Madagascar reef were dominated by macroalgae and seconded by octocorals. However, the shallow rocky environments of the reef crest had the highest richness of habitat-forming groups of organisms; here, we registered high abundances of octocorals and macroalgae, with sponges, Millepora alcicornis and zoantharians dominating in some patches, creating high levels of habitat heterogeneity. IDW and OK generated similar maps of distribution for all the taxa; however, cross-validation tests showed that IDW outperformed OK in the prediction of their abundances. When the sampling distance was at 20 m, both interpolation techniques performed poorly, but as the sampling was done at shorter distances prediction accuracies increased, especially for IDW. OK had higher mean prediction errors and failed to correctly interpolate the highest abundance values measured in situ, except for macroalgae, whereas IDW had lower mean prediction errors and high correlations between predicted and measured values in all cases when sampling was every 5 m. The accurate spatial interpolations created using IDW allowed us to see the spatial variability of each taxa at a biological and spatial resolution that remote sensing would not have been able to produce. Our study sets the basis for further research projects and conservation management in Madagascar reef and encourages similar studies in the region and other parts of the world where remote sensing technologies are not suitable for use. PMID:29204321
Hay, L.E.; Clark, M.P.
2003-01-01
This paper examines the hydrologic model performance in three snowmelt-dominated basins in the western United States to dynamically- and statistically downscaled output from the National Centers for Environmental Prediction/National Center for Atmospheric Research Reanalysis (NCEP). Runoff produced using a distributed hydrologic model is compared using daily precipitation and maximum and minimum temperature timeseries derived from the following sources: (1) NCEP output (horizontal grid spacing of approximately 210 km); (2) dynamically downscaled (DDS) NCEP output using a Regional Climate Model (RegCM2, horizontal grid spacing of approximately 52 km); (3) statistically downscaled (SDS) NCEP output; (4) spatially averaged measured data used to calibrate the hydrologic model (Best-Sta) and (5) spatially averaged measured data derived from stations located within the area of the RegCM2 model output used for each basin, but excluding Best-Sta set (All-Sta). In all three basins the SDS-based simulations of daily runoff were as good as runoff produced using the Best-Sta timeseries. The NCEP, DDS, and All-Sta timeseries were able to capture the gross aspects of the seasonal cycles of precipitation and temperature. However, in all three basins, the NCEP-, DDS-, and All-Sta-based simulations of runoff showed little skill on a daily basis. When the precipitation and temperature biases were corrected in the NCEP, DDS, and All-Sta timeseries, the accuracy of the daily runoff simulations improved dramatically, but, with the exception of the bias-corrected All-Sta data set, these simulations were never as accurate as the SDS-based simulations. This need for a bias correction may be somewhat troubling, but in the case of the large station-timeseries (All-Sta), the bias correction did indeed 'correct' for the change in scale. It is unknown if bias corrections to model output will be valid in a future climate. Future work is warranted to identify the causes for (and removal of) systematic biases in DDS simulations, and improve DDS simulations of daily variability in local climate. Until then, SDS based simulations of runoff appear to be the safer downscaling choice.
WIYN Open Cluster Study. XXXII. Stellar Radial Velocities in the Old Open Cluster NGC 188
NASA Astrophysics Data System (ADS)
Geller, Aaron M.; Mathieu, Robert D.; Harris, Hugh C.; McClure, Robert D.
2008-06-01
We present the results of our ongoing radial-velocity (RV) survey of the old (7 Gyr) open cluster NGC 188. Our WIYN 3.5 m data set spans a time baseline of 11 years, a magnitude range of 12 <= V <= 16.5 (1.18-0.94 M sun), and a 1° diameter region on the sky. With the addition of a Domain Astrophysical Observatory data set we extend our bright limit to V = 10.8 and, for some stars, extend our time baseline to 35 years. Our magnitude limits include solar-mass main-sequence stars, subgiants, giants, and blue stragglers (BSs), and our spatial coverage extends radially to 17 pc (~13 core radii). For the WIYN data we present a detailed description of our data reduction process and a thorough analysis of our measurement precision of 0.4 km s-1 for narrow-lined stars. We have measured radial velocities for 1046 stars in the direction of NGC 188, and have calculated RV membership probabilities for stars with >=3 measurements, finding 473 to be likely cluster members. We detect 124 velocity-variable cluster members, all of which are likely to be dynamically hard-binary stars. Using our single member stars, we find an average cluster radial velocity of -42.36 ± 0.04 km s-1. We use our precise RV and proper-motion membership data to greatly reduce field-star contamination in our cleaned color-magnitude diagram, from which we identify six stars of note that lie far from a standard single-star isochrone. We present a detailed study of the spatial distribution of cluster-member populations, and find the binaries to be centrally concentrated, providing evidence for the presence of mass segregation in NGC 188. We observe the BSs to populate a bimodal spatial distribution that is not centrally concentrated, suggesting that we may be observing two populations of BSs in NGC 188, including a centrally concentrated distribution as well as a halo population. Finally, we find NGC 188 to have a global RV dispersion of 0.64 ± 0.04 km s-1, which may be inflated by up to 0.23 km s-1 from unresolved binaries. When corrected for unresolved binaries, the NGC 188 RV dispersion has a nearly isothermal radial distribution. We use this mean-corrected velocity dispersion to derive a virial mass of 2300 ± 460 M sun .
Jacob, Benjamin G; Griffith, Daniel A; Muturi, Ephantus J; Caamano, Erick X; Githure, John I; Novak, Robert J
2009-01-01
Background Autoregressive regression coefficients for Anopheles arabiensis aquatic habitat models are usually assessed using global error techniques and are reported as error covariance matrices. A global statistic, however, will summarize error estimates from multiple habitat locations. This makes it difficult to identify where there are clusters of An. arabiensis aquatic habitats of acceptable prediction. It is therefore useful to conduct some form of spatial error analysis to detect clusters of An. arabiensis aquatic habitats based on uncertainty residuals from individual sampled habitats. In this research, a method of error estimation for spatial simulation models was demonstrated using autocorrelation indices and eigenfunction spatial filters to distinguish among the effects of parameter uncertainty on a stochastic simulation of ecological sampled Anopheles aquatic habitat covariates. A test for diagnostic checking error residuals in an An. arabiensis aquatic habitat model may enable intervention efforts targeting productive habitats clusters, based on larval/pupal productivity, by using the asymptotic distribution of parameter estimates from a residual autocovariance matrix. The models considered in this research extends a normal regression analysis previously considered in the literature. Methods Field and remote-sampled data were collected during July 2006 to December 2007 in Karima rice-village complex in Mwea, Kenya. SAS 9.1.4® was used to explore univariate statistics, correlations, distributions, and to generate global autocorrelation statistics from the ecological sampled datasets. A local autocorrelation index was also generated using spatial covariance parameters (i.e., Moran's Indices) in a SAS/GIS® database. The Moran's statistic was decomposed into orthogonal and uncorrelated synthetic map pattern components using a Poisson model with a gamma-distributed mean (i.e. negative binomial regression). The eigenfunction values from the spatial configuration matrices were then used to define expectations for prior distributions using a Markov chain Monte Carlo (MCMC) algorithm. A set of posterior means were defined in WinBUGS 1.4.3®. After the model had converged, samples from the conditional distributions were used to summarize the posterior distribution of the parameters. Thereafter, a spatial residual trend analyses was used to evaluate variance uncertainty propagation in the model using an autocovariance error matrix. Results By specifying coefficient estimates in a Bayesian framework, the covariate number of tillers was found to be a significant predictor, positively associated with An. arabiensis aquatic habitats. The spatial filter models accounted for approximately 19% redundant locational information in the ecological sampled An. arabiensis aquatic habitat data. In the residual error estimation model there was significant positive autocorrelation (i.e., clustering of habitats in geographic space) based on log-transformed larval/pupal data and the sampled covariate depth of habitat. Conclusion An autocorrelation error covariance matrix and a spatial filter analyses can prioritize mosquito control strategies by providing a computationally attractive and feasible description of variance uncertainty estimates for correctly identifying clusters of prolific An. arabiensis aquatic habitats based on larval/pupal productivity. PMID:19772590
NASA Astrophysics Data System (ADS)
Shao, Honglan; Xie, Feng; Liu, Chengyu; Liu, Zhihui; Zhang, Changxing; Yang, Gui; Wang, Jianyu
2016-04-01
The cooling water discharged from the coastal plants flow into the sea continuously, whose temperature is higher than original sea surface temperature (SST). The fact will have non-negligible influence on the marine environment in and around where the plants site. Hence, it's significant to monitor the temporal and spatial variation of the warm-water discharge for the assessment of the effect of the plant on its surrounding marine environment. The paper describes an approach for the dynamic monitoring of the warm-water discharge of coastal plants based on the airborne high-resolution thermal infrared remote sensing technology. Firstly, the geometric correction was carried out for the thermal infrared remote sensing images acquired on the aircraft. Secondly, the atmospheric correction method was used to retrieve the sea surface temperature of the images. Thirdly, the temperature-rising districts caused by the warm-water discharge were extracted. Lastly, the temporal and spatial variations of the warm-water discharge were analyzed through the geographic information system (GIS) technology. The approach was applied to Qinshan nuclear power plant (NPP), in Zhejiang Province, China. In considering with the tide states, the diffusion, distribution and temperature-rising values of the warm-water discharged from the plant were calculated and analyzed, which are useful to the marine environment assessment.
Projecting climate change impacts on hydrology: the potential role of daily GCM output
NASA Astrophysics Data System (ADS)
Maurer, E. P.; Hidalgo, H. G.; Das, T.; Dettinger, M. D.; Cayan, D.
2008-12-01
A primary challenge facing resource managers in accommodating climate change is determining the range and uncertainty in regional and local climate projections. This is especially important for assessing changes in extreme events, which will drive many of the more severe impacts of a changed climate. Since global climate models (GCMs) produce output at a spatial scale incompatible with local impact assessment, different techniques have evolved to downscale GCM output so locally important climate features are expressed in the projections. We compared skill and hydrologic projections using two statistical downscaling methods and a distributed hydrology model. The downscaling methods are the constructed analogues (CA) and the bias correction and spatial downscaling (BCSD). CA uses daily GCM output, and can thus capture GCM projections for changing extreme event occurrence, while BCSD uses monthly output and statistically generates historical daily sequences. We evaluate the hydrologic impacts projected using downscaled climate (from the NCEP/NCAR reanalysis as a surrogate GCM) for the late 20th century with both methods, comparing skill in projecting soil moisture, snow pack, and streamflow at key locations in the Western United States. We include an assessment of a new method for correcting for GCM biases in a hybrid method combining the most important characteristics of both methods.
Correction of small imperfections on white glazed china surfaces by laser radiation
NASA Astrophysics Data System (ADS)
Képíró, I.; Osvay, K.; Divall, M.
2007-07-01
A laser-assisted technique has been developed for correction of small diameter (1 mm) and shallow (0.5 mm) imperfections on the surface of gloss fired porcelain. To study the physics and establish the important parameters, artificially made holes in a porcelain sample have been first filled with correction material, then covered with raw glaze and treated by a pulsed, 7 kHz repetition rate CO 2 laser at 10.6 μm. The modification of the surface and the surrounding area have been quantified and studied with a large range of parameters of incident laser power (1-10 W), width of the laser pulses (10-125 μs) and duration of laser heating (60-480 s). Although the shine of the treated area, defined as the distribution of micro-droplets on the surface, is very similar to the untreated surfaces, the surroundings of the treated area usually show cracks. The measurement of both the spatial temperature distribution and the temporal cooling rate of the treated surface has revealed that a simple melting process always results in high gradient temperature distribution within the irradiated zone. Its inhomogeneous and fast cooling always generate at least micro-cracks on the surface within a few seconds after the laser was turned off. The duration and intensity of the laser irradiation have been then optimized in order to achieve the fastest possible melting of the surface, but without producing such high temperature gradients. To eliminate the cracks, more elaborated pre-heating and slowed-cooling-rate processes have been tried with prosperous results. These achievements complete our previous study, making possible to repair the most common surface imperfections and holes of gloss fired china samples.
Evaluation of Bias Correction Method for Satellite-Based Rainfall Data
Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter
2016-01-01
With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration’s (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003–2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW’s) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach. PMID:27314363
Evaluation of Bias Correction Method for Satellite-Based Rainfall Data.
Bhatti, Haris Akram; Rientjes, Tom; Haile, Alemseged Tamiru; Habib, Emad; Verhoef, Wouter
2016-06-15
With the advances in remote sensing technology, satellite-based rainfall estimates are gaining attraction in the field of hydrology, particularly in rainfall-runoff modeling. Since estimates are affected by errors correction is required. In this study, we tested the high resolution National Oceanic and Atmospheric Administration's (NOAA) Climate Prediction Centre (CPC) morphing technique (CMORPH) satellite rainfall product (CMORPH) in the Gilgel Abbey catchment, Ethiopia. CMORPH data at 8 km-30 min resolution is aggregated to daily to match in-situ observations for the period 2003-2010. Study objectives are to assess bias of the satellite estimates, to identify optimum window size for application of bias correction and to test effectiveness of bias correction. Bias correction factors are calculated for moving window (MW) sizes and for sequential windows (SW's) of 3, 5, 7, 9, …, 31 days with the aim to assess error distribution between the in-situ observations and CMORPH estimates. We tested forward, central and backward window (FW, CW and BW) schemes to assess the effect of time integration on accumulated rainfall. Accuracy of cumulative rainfall depth is assessed by Root Mean Squared Error (RMSE). To systematically correct all CMORPH estimates, station based bias factors are spatially interpolated to yield a bias factor map. Reliability of interpolation is assessed by cross validation. The uncorrected CMORPH rainfall images are multiplied by the interpolated bias map to result in bias corrected CMORPH estimates. Findings are evaluated by RMSE, correlation coefficient (r) and standard deviation (SD). Results showed existence of bias in the CMORPH rainfall. It is found that the 7 days SW approach performs best for bias correction of CMORPH rainfall. The outcome of this study showed the efficiency of our bias correction approach.
NASA Astrophysics Data System (ADS)
Fricke, Katharina; Baschek, Björn; Jenal, Alexander; Kneer, Caspar; Weber, Immanuel; Bongartz, Jens; Wyrwa, Jens; Schöl, Andreas
2016-10-01
This study presents the results from a combined aerial survey performed with a hexacopter and a gyrocopter over a part of the Elbe estuary near Hamburg, Germany. The survey was conducted by the Federal Institute of Hydrology, Germany, and the Fraunhofer Application Center for Multimodal and Airborne Sensors as well as by a contracted engineering company with the aim to acquire spatial thermal infrared (TIR) data of the Hahnöfer Nebenelbe, a branch of the Elbe estuary. Additionally, RGB and NIR data was captured to facilitate the identification of water surfaces and intertidal mudflats. The temperature distribution of the Elbe estuary affects all biological processes and in consequence the oxygen content, which is a key parameter in water quality. The oxygen levels vary in space between the main fairway and side channels. So far, only point measurements are available for monitoring and calibration/validation of water quality models. To better represent this highly dynamic system with a high spatial and temporal variability, tidal streams, heating and cooling, diffusion and mixing processes, spatially distributed data from several points of time within the tidal cycle are necessary. The data acquisition took place during two tidal cycles over two subsequent days in the summer of 2015. While the piloted gyrocopter covered the whole Hahnöfer Nebenelbe seven times, the unmanned hexacopter covered a smaller section of the branch and tidal mudflats with a higher spatial and temporal resolution (16 coverages of the subarea). The gyrocopter data was acquired with a thermal imaging system and processed and georeferenced using the structure from motion algorithm with GPS information from the gyrocopter and optional ground control points. The hexacopter data was referenced based on ground control points and the GPS and position information of the acquisition system. Both datasets from the gyrocopter and the hexacopter are corrected for the effects of the atmosphere and emissivity of the water surface and compared to in situ measurements, taken during the data acquisition. Of particular interest is the effect of the observation angle on the brightness temperature acquired by the wide angle lenses on the platforms, which is up to 40° at the margins of the imagery. Here, both datasets show deviating temperatures, which are probably not due to actual temperature differences. We will discuss the position accuracy achieved over the water areas, the adaptation of atmospheric and emissivity correction to the observation angle and subsequent improvement of the temperature data. With two datasets of the same research area at different resolutions we will investigate the effects of the acquisition platforms, acquisition system and resolutions on the accuracy of the remotely sensed temperatures as well as their ability to represent temperature patterns of tidal currents and mixing processes.
Mazoure, Bogdan; Caraus, Iurie; Nadon, Robert; Makarenkov, Vladimir
2018-06-01
Data generated by high-throughput screening (HTS) technologies are prone to spatial bias. Traditionally, bias correction methods used in HTS assume either a simple additive or, more recently, a simple multiplicative spatial bias model. These models do not, however, always provide an accurate correction of measurements in wells located at the intersection of rows and columns affected by spatial bias. The measurements in these wells depend on the nature of interaction between the involved biases. Here, we propose two novel additive and two novel multiplicative spatial bias models accounting for different types of bias interactions. We describe a statistical procedure that allows for detecting and removing different types of additive and multiplicative spatial biases from multiwell plates. We show how this procedure can be applied by analyzing data generated by the four HTS technologies (homogeneous, microorganism, cell-based, and gene expression HTS), the three high-content screening (HCS) technologies (area, intensity, and cell-count HCS), and the only small-molecule microarray technology available in the ChemBank small-molecule screening database. The proposed methods are included in the AssayCorrector program, implemented in R, and available on CRAN.
NASA Technical Reports Server (NTRS)
Welton, Ellsworth J.; Ginoux, Paul; Colarco, Peter; Chin, Mian; Spinhirne, James D.; Palm, Steven P.; Hlavka, Dennis; Hart, William
2003-01-01
In the past, satellite measurements of aerosols have only been possible using passive sensors. Analysis of passive satellite data has lead to an improved understanding of aerosol properties, spatial distribution, and their effect on the earth s climate. However, direct measurement of aerosol vertical distribution has not been possible using only the passive data. Knowledge of aerosol vertical distribution is important to correctly assess the impact of aerosol absorption, for certain atmospheric correction procedures, and to help constrain height profiles in aerosol transport models. On January 12,2003 NASA launched the first satellite-based lidar, the Geoscience Laser Altimeter System (GLAS), onboard the ICESat spacecraft. GLAS is both an altimeter and an atmospheric lidar, and obtains direct measurements of aerosol and cloud heights. Here we show an overview of GLAS, provide an update of its current status, and discuss how GUS data will be useful for modeling efforts. In particular, a strategy of using GLAS to characterize the height profile of dust plumes over source regions will be presented, along with initial results. Such information can be used to validate and improve output from aerosol transport models. Aerosol height profile comparisons between GLAS and transport models will be shown for regions downwind of aerosol sources. We will also discuss the feasibility of assimilating GLAS profiles into the models in order to improve their output,
NASA Technical Reports Server (NTRS)
Welton, E. J.; Spinhime, J.; Palm, S.; Hlavka, D.; Hart, W.; Ginoux, P.; Chin, M.; Colarco, P.
2004-01-01
In the past, satellite measurements of aerosols have only been possible using passive sensors. Analysis of passive satellite data has lead to an improved understanding of aerosol properties, spatial distribution, and their effect on the earth,s climate. However, direct measurement of aerosol vertical distribution has not been possible using only the passive data. Knowledge of aerosol vertical distribution is important to correctly assess the impact of aerosol absorption, for certain atmospheric correction procedures, and to help constrain height profiles in aerosol transport models. On January 12,2003 NASA launched the first satellite-based lidar, the Geoscience Laser Altimeter System (GLAS), onboard the ICESat spacecraft. GLAS is both an altimeter and an atmospheric lidar, and obtains direct measurements of aerosol and cloud heights. Here we show an overview of GLAS, provide an update of its current status, and discuss how GLAS data will be useful for modeling efforts. In particular, a strategy of using GLAS to characterize the height profile of dust plumes over source regions will be presented, along with initial results. Such information can be used to validate and improve output from aerosol transport models. Aerosol height profile comparisons between GLAS and transport models will be shown for regions downwind of aerosol sources. We will also discuss the feasibility of assimilating GLAS profiles into the models in order to improve their output.
Progress toward accurate high spatial resolution actinide analysis by EPMA
NASA Astrophysics Data System (ADS)
Jercinovic, M. J.; Allaz, J. M.; Williams, M. L.
2010-12-01
High precision, high spatial resolution EPMA of actinides is a significant issue for geochronology, resource geochemistry, and studies involving the nuclear fuel cycle. Particular interest focuses on understanding of the behavior of Th and U in the growth and breakdown reactions relevant to actinide-bearing phases (monazite, zircon, thorite, allanite, etc.), and geochemical fractionation processes involving Th and U in fluid interactions. Unfortunately, the measurement of minor and trace concentrations of U in the presence of major concentrations of Th and/or REEs is particularly problematic, especially in complexly zoned phases with large compositional variation on the micro or nanoscale - spatial resolutions now accessible with modern instruments. Sub-micron, high precision compositional analysis of minor components is feasible in very high Z phases where scattering is limited at lower kV (15kV or less) and where the beam diameter can be kept below 400nm at high current (e.g. 200-500nA). High collection efficiency spectrometers and high performance electron optics in EPMA now allow the use of lower overvoltage through an exceptional range in beam current, facilitating higher spatial resolution quantitative analysis. The U LIII edge at 17.2 kV precludes L-series analysis at low kV (high spatial resolution), requiring careful measurements of the actinide M series. Also, U-La detection (wavelength = 0.9A) requires the use of LiF (220) or (420), not generally available on most instruments. Strong peak overlaps of Th on U make highly accurate interference correction mandatory, with problems compounded by the ThMIV and ThMV absorption edges affecting peak, background, and interference calibration measurements (especially the interference of the Th M line family on UMb). Complex REE bearing phases such as monazite, zircon, and allanite have particularly complex interference issues due to multiple peak and background overlaps from elements present in the activation volume, as well as interferences from fluorescence at a distance from adjacent phases or distinct compositional domains in the same phase. Interference corrections for elements detected during boundary fluorescence are further complicated by X-ray focusing geometry considerations. Additional complications arise from the high current densities required for high spatial resolution and high count precision, such as fluctuations in internal charge distribution and peak shape changes as satellite production efficiency varies from calibration to analysis. No flawless method has yet emerged. Extreme care in interference corrections, especially where multiple and sometime mutual overlaps are present, and maximum care (and precision) in background characterization to account for interferences and curvature (e.g., WDS scan or multipoint regression), are crucial developments. Calibration curves from multiple peak and interference calibration measurements at different concentrations, and iterative software methodologies for incorporating absorption edge effects, and non-linearities in interference corrections due to peak shape changes and off-axis X-ray defocussing during boundary fluorescence at a distance, are directions with significant potential.
Balanced cortical microcircuitry for spatial working memory based on corrective feedback control.
Lim, Sukbin; Goldman, Mark S
2014-05-14
A hallmark of working memory is the ability to maintain graded representations of both the spatial location and amplitude of a memorized stimulus. Previous work has identified a neural correlate of spatial working memory in the persistent maintenance of spatially specific patterns of neural activity. How such activity is maintained by neocortical circuits remains unknown. Traditional models of working memory maintain analog representations of either the spatial location or the amplitude of a stimulus, but not both. Furthermore, although most previous models require local excitation and lateral inhibition to maintain spatially localized persistent activity stably, the substrate for lateral inhibitory feedback pathways is unclear. Here, we suggest an alternative model for spatial working memory that is capable of maintaining analog representations of both the spatial location and amplitude of a stimulus, and that does not rely on long-range feedback inhibition. The model consists of a functionally columnar network of recurrently connected excitatory and inhibitory neural populations. When excitation and inhibition are balanced in strength but offset in time, drifts in activity trigger spatially specific negative feedback that corrects memory decay. The resulting networks can temporally integrate inputs at any spatial location, are robust against many commonly considered perturbations in network parameters, and, when implemented in a spiking model, generate irregular neural firing characteristic of that observed experimentally during persistent activity. This work suggests balanced excitatory-inhibitory memory circuits implementing corrective negative feedback as a substrate for spatial working memory. Copyright © 2014 the authors 0270-6474/14/346790-17$15.00/0.
Scatter characterization and correction for simultaneous multiple small-animal PET imaging.
Prasad, Rameshwar; Zaidi, Habib
2014-04-01
The rapid growth and usage of small-animal positron emission tomography (PET) in molecular imaging research has led to increased demand on PET scanner's time. One potential solution to increase throughput is to scan multiple rodents simultaneously. However, this is achieved at the expense of deterioration of image quality and loss of quantitative accuracy owing to enhanced effects of photon attenuation and Compton scattering. The purpose of this work is, first, to characterize the magnitude and spatial distribution of the scatter component in small-animal PET imaging when scanning single and multiple rodents simultaneously and, second, to assess the relevance and evaluate the performance of scatter correction under similar conditions. The LabPET™-8 scanner was modelled as realistically as possible using Geant4 Application for Tomographic Emission Monte Carlo simulation platform. Monte Carlo simulations allow the separation of unscattered and scattered coincidences and as such enable detailed assessment of the scatter component and its origin. Simple shape-based and more realistic voxel-based phantoms were used to simulate single and multiple PET imaging studies. The modelled scatter component using the single-scatter simulation technique was compared to Monte Carlo simulation results. PET images were also corrected for attenuation and the combined effect of attenuation and scatter on single and multiple small-animal PET imaging evaluated in terms of image quality and quantitative accuracy. A good agreement was observed between calculated and Monte Carlo simulated scatter profiles for single- and multiple-subject imaging. In the LabPET™-8 scanner, the detector covering material (kovar) contributed the maximum amount of scatter events while the scatter contribution due to lead shielding is negligible. The out-of field-of-view (FOV) scatter fraction (SF) is 1.70, 0.76, and 0.11% for lower energy thresholds of 250, 350, and 400 keV, respectively. The increase in SF ranged between 25 and 64% when imaging multiple subjects (three to five) of different size simultaneously in comparison to imaging a single subject. The spill-over ratio (SOR) increases with increasing the number of subjects in the FOV. Scatter correction improved the SOR for both water and air cold compartments of single and multiple imaging studies. The recovery coefficients for different body parts of the mouse whole-body and rat whole-body anatomical models were improved for multiple imaging studies following scatter correction. The magnitude and spatial distribution of the scatter component in small-animal PET imaging of single and multiple subjects simultaneously were characterized, and its impact was evaluated in different situations. Scatter correction improves PET image quality and quantitative accuracy for single rat and simultaneous multiple mice and rat imaging studies, whereas its impact is insignificant in single mouse imaging.
Inoue, Makoto; Morino, Isamu; Uchino, Osamu; ...
2016-08-01
We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO 2 (XCO 2) and CH 4 (XCH 4) derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT). We conduct correlation analyses between the GOSAT biases and simultaneously retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from the Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the uncorrected/corrected GOSAT data were compared to independent XCO 2more » and XCH 4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole-to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically derived bias correction improves the agreement between GOSAT XCO 2/XCH 4 and the aircraft data. Finally, we present spatial distributions and temporal variations of the derived GOSAT biases.« less
DOE Office of Scientific and Technical Information (OSTI.GOV)
Inoue, Makoto; Morino, Isamu; Uchino, Osamu
We describe a method for removing systematic biases of column-averaged dry air mole fractions of CO 2 (XCO 2) and CH 4 (XCH 4) derived from short-wavelength infrared (SWIR) spectra of the Greenhouse gases Observing SATellite (GOSAT). We conduct correlation analyses between the GOSAT biases and simultaneously retrieved auxiliary parameters. We use these correlations to bias correct the GOSAT data, removing these spurious correlations. Data from the Total Carbon Column Observing Network (TCCON) were used as reference values for this regression analysis. To evaluate the effectiveness of this correction method, the uncorrected/corrected GOSAT data were compared to independent XCO 2more » and XCH 4 data derived from aircraft measurements taken for the Comprehensive Observation Network for TRace gases by AIrLiner (CONTRAIL) project, the National Oceanic and Atmospheric Administration (NOAA), the US Department of Energy (DOE), the National Institute for Environmental Studies (NIES), the Japan Meteorological Agency (JMA), the HIAPER Pole-to-Pole observations (HIPPO) program, and the GOSAT validation aircraft observation campaign over Japan. These comparisons demonstrate that the empirically derived bias correction improves the agreement between GOSAT XCO 2/XCH 4 and the aircraft data. Finally, we present spatial distributions and temporal variations of the derived GOSAT biases.« less
Fixed Pattern Noise pixel-wise linear correction for crime scene imaging CMOS sensor
NASA Astrophysics Data System (ADS)
Yang, Jie; Messinger, David W.; Dube, Roger R.; Ientilucci, Emmett J.
2017-05-01
Filtered multispectral imaging technique might be a potential method for crime scene documentation and evidence detection due to its abundant spectral information as well as non-contact and non-destructive nature. Low-cost and portable multispectral crime scene imaging device would be highly useful and efficient. The second generation crime scene imaging system uses CMOS imaging sensor to capture spatial scene and bandpass Interference Filters (IFs) to capture spectral information. Unfortunately CMOS sensors suffer from severe spatial non-uniformity compared to CCD sensors and the major cause is Fixed Pattern Noise (FPN). IFs suffer from "blue shift" effect and introduce spatial-spectral correlated errors. Therefore, Fixed Pattern Noise (FPN) correction is critical to enhance crime scene image quality and is also helpful for spatial-spectral noise de-correlation. In this paper, a pixel-wise linear radiance to Digital Count (DC) conversion model is constructed for crime scene imaging CMOS sensor. Pixel-wise conversion gain Gi,j and Dark Signal Non-Uniformity (DSNU) Zi,j are calculated. Also, conversion gain is divided into four components: FPN row component, FPN column component, defects component and effective photo response signal component. Conversion gain is then corrected to average FPN column and row components and defects component so that the sensor conversion gain is uniform. Based on corrected conversion gain and estimated image incident radiance from the reverse of pixel-wise linear radiance to DC model, corrected image spatial uniformity can be enhanced to 7 times as raw image, and the bigger the image DC value within its dynamic range, the better the enhancement.
Takegata, Rika; Brattico, Elvira; Tervaniemi, Mari; Varyagina, Olga; Näätänen, Risto; Winkler, István
2005-09-01
The role of attention in conjoining features of an object has been a topic of much debate. Studies using the mismatch negativity (MMN), an index of detecting acoustic deviance, suggested that the conjunctions of auditory features are preattentively represented in the brain. These studies, however, used sequentially presented sounds and thus are not directly comparable with visual studies of feature integration. Therefore, the current study presented an array of spatially distributed sounds to determine whether the auditory features of concurrent sounds are correctly conjoined without focal attention directed to the sounds. Two types of sounds differing from each other in timbre and pitch were repeatedly presented together while subjects were engaged in a visual n-back working-memory task and ignored the sounds. Occasional reversals of the frequent pitch-timbre combinations elicited MMNs of a very similar amplitude and latency irrespective of the task load. This result suggested preattentive integration of auditory features. However, performance in a subsequent target-search task with the same stimuli indicated the occurrence of illusory conjunctions. The discrepancy between the results obtained with and without focal attention suggests that illusory conjunctions may occur during voluntary access to the preattentively encoded object representations.
Bias correction of surface downwelling longwave and shortwave radiation for the EWEMBI dataset
NASA Astrophysics Data System (ADS)
Lange, Stefan
2018-05-01
Many meteorological forcing datasets include bias-corrected surface downwelling longwave and shortwave radiation (rlds and rsds). Methods used for such bias corrections range from multi-year monthly mean value scaling to quantile mapping at the daily timescale. An additional downscaling is necessary if the data to be corrected have a higher spatial resolution than the observational data used to determine the biases. This was the case when EartH2Observe (E2OBS; Calton et al., 2016) rlds and rsds were bias-corrected using more coarsely resolved Surface Radiation Budget (SRB; Stackhouse Jr. et al., 2011) data for the production of the meteorological forcing dataset EWEMBI (Lange, 2016). This article systematically compares various parametric quantile mapping methods designed specifically for this purpose, including those used for the production of EWEMBI rlds and rsds. The methods vary in the timescale at which they operate, in their way of accounting for physical upper radiation limits, and in their approach to bridging the spatial resolution gap between E2OBS and SRB. It is shown how temporal and spatial variability deflation related to bilinear interpolation and other deterministic downscaling approaches can be overcome by downscaling the target statistics of quantile mapping from the SRB to the E2OBS grid such that the sub-SRB-grid-scale spatial variability present in the original E2OBS data is retained. Cross validations at the daily and monthly timescales reveal that it is worthwhile to take empirical estimates of physical upper limits into account when adjusting either radiation component and that, overall, bias correction at the daily timescale is more effective than bias correction at the monthly timescale if sampling errors are taken into account.
Interannual Change Detection of Mediterranean Seagrasses Using RapidEye Image Time Series
Traganos, Dimosthenis; Reinartz, Peter
2018-01-01
Recent research studies have highlighted the decrease in the coverage of Mediterranean seagrasses due to mainly anthropogenic activities. The lack of data on the distribution of these significant aquatic plants complicates the quantification of their decreasing tendency. While Mediterranean seagrasses are declining, satellite remote sensing technology is growing at an unprecedented pace, resulting in a wealth of spaceborne image time series. Here, we exploit recent advances in high spatial resolution sensors and machine learning to study Mediterranean seagrasses. We process a multispectral RapidEye time series between 2011 and 2016 to detect interannual seagrass dynamics in 888 submerged hectares of the Thermaikos Gulf, NW Aegean Sea, Greece (eastern Mediterranean Sea). We assess the extent change of two Mediterranean seagrass species, the dominant Posidonia oceanica and Cymodocea nodosa, following atmospheric and analytical water column correction, as well as machine learning classification, using Random Forests, of the RapidEye time series. Prior corrections are necessary to untangle the initially weak signal of the submerged seagrass habitats from satellite imagery. The central results of this study show that P. oceanica seagrass area has declined by 4.1%, with a trend of −11.2 ha/yr, while C. nodosa seagrass area has increased by 17.7% with a trend of +18 ha/yr throughout the 5-year study period. Trends of change in spatial distribution of seagrasses in the Thermaikos Gulf site are in line with reported trends in the Mediterranean. Our presented methodology could be a time- and cost-effective method toward the quantitative ecological assessment of seagrass dynamics elsewhere in the future. From small meadows to whole coastlines, knowledge of aquatic plant dynamics could resolve decline or growth trends and accurately highlight key units for future restoration, management, and conservation. PMID:29467777
Interannual Change Detection of Mediterranean Seagrasses Using RapidEye Image Time Series.
Traganos, Dimosthenis; Reinartz, Peter
2018-01-01
Recent research studies have highlighted the decrease in the coverage of Mediterranean seagrasses due to mainly anthropogenic activities. The lack of data on the distribution of these significant aquatic plants complicates the quantification of their decreasing tendency. While Mediterranean seagrasses are declining, satellite remote sensing technology is growing at an unprecedented pace, resulting in a wealth of spaceborne image time series. Here, we exploit recent advances in high spatial resolution sensors and machine learning to study Mediterranean seagrasses. We process a multispectral RapidEye time series between 2011 and 2016 to detect interannual seagrass dynamics in 888 submerged hectares of the Thermaikos Gulf, NW Aegean Sea, Greece (eastern Mediterranean Sea). We assess the extent change of two Mediterranean seagrass species, the dominant Posidonia oceanica and Cymodocea nodosa , following atmospheric and analytical water column correction, as well as machine learning classification, using Random Forests, of the RapidEye time series. Prior corrections are necessary to untangle the initially weak signal of the submerged seagrass habitats from satellite imagery. The central results of this study show that P. oceanica seagrass area has declined by 4.1%, with a trend of -11.2 ha/yr, while C. nodosa seagrass area has increased by 17.7% with a trend of +18 ha/yr throughout the 5-year study period. Trends of change in spatial distribution of seagrasses in the Thermaikos Gulf site are in line with reported trends in the Mediterranean. Our presented methodology could be a time- and cost-effective method toward the quantitative ecological assessment of seagrass dynamics elsewhere in the future. From small meadows to whole coastlines, knowledge of aquatic plant dynamics could resolve decline or growth trends and accurately highlight key units for future restoration, management, and conservation.
The effects of spatial population dataset choice on estimates of population at risk of disease
2011-01-01
Background The spatial modeling of infectious disease distributions and dynamics is increasingly being undertaken for health services planning and disease control monitoring, implementation, and evaluation. Where risks are heterogeneous in space or dependent on person-to-person transmission, spatial data on human population distributions are required to estimate infectious disease risks, burdens, and dynamics. Several different modeled human population distribution datasets are available and widely used, but the disparities among them and the implications for enumerating disease burdens and populations at risk have not been considered systematically. Here, we quantify some of these effects using global estimates of populations at risk (PAR) of P. falciparum malaria as an example. Methods The recent construction of a global map of P. falciparum malaria endemicity enabled the testing of different gridded population datasets for providing estimates of PAR by endemicity class. The estimated population numbers within each class were calculated for each country using four different global gridded human population datasets: GRUMP (~1 km spatial resolution), LandScan (~1 km), UNEP Global Population Databases (~5 km), and GPW3 (~5 km). More detailed assessments of PAR variation and accuracy were conducted for three African countries where census data were available at a higher administrative-unit level than used by any of the four gridded population datasets. Results The estimates of PAR based on the datasets varied by more than 10 million people for some countries, even accounting for the fact that estimates of population totals made by different agencies are used to correct national totals in these datasets and can vary by more than 5% for many low-income countries. In many cases, these variations in PAR estimates comprised more than 10% of the total national population. The detailed country-level assessments suggested that none of the datasets was consistently more accurate than the others in estimating PAR. The sizes of such differences among modeled human populations were related to variations in the methods, input resolution, and date of the census data underlying each dataset. Data quality varied from country to country within the spatial population datasets. Conclusions Detailed, highly spatially resolved human population data are an essential resource for planning health service delivery for disease control, for the spatial modeling of epidemics, and for decision-making processes related to public health. However, our results highlight that for the low-income regions of the world where disease burden is greatest, existing datasets display substantial variations in estimated population distributions, resulting in uncertainty in disease assessments that utilize them. Increased efforts are required to gather contemporary and spatially detailed demographic data to reduce this uncertainty, particularly in Africa, and to develop population distribution modeling methods that match the rigor, sophistication, and ability to handle uncertainty of contemporary disease mapping and spread modeling. In the meantime, studies that utilize a particular spatial population dataset need to acknowledge the uncertainties inherent within them and consider how the methods and data that comprise each will affect conclusions. PMID:21299885
NASA Technical Reports Server (NTRS)
Robinson, Wayne D.; Kummerrow, Christian; Olson, William S.
1992-01-01
A correction technique is presented for matching the resolution of all the frequencies of the satelliteborne Special Sensor Microwave/Imager (SSM/I) to the about-25-km spatial resolution of the 37-GHz channel. This entails, on the one hand, the enhancement of the spatial resolution of the 19- and 22-GHz channels, and on the other, the degrading of that of the 85-GHz channel. The Backus and Gilbert (1970) approach is found to yield sufficient spatial resolution to render such a correction worthwhile.
Quantile Mapping Bias correction for daily precipitation over Vietnam in a regional climate model
NASA Astrophysics Data System (ADS)
Trinh, L. T.; Matsumoto, J.; Ngo-Duc, T.
2017-12-01
In the past decades, Regional Climate Models (RCMs) have been developed significantly, allowing climate simulation to be conducted at a higher resolution. However, RCMs often contained biases when comparing with observations. Therefore, statistical correction methods were commonly employed to reduce/minimize the model biases. In this study, outputs of the Regional Climate Model (RegCM) version 4.3 driven by the CNRM-CM5 global products were evaluated with and without the Quantile Mapping (QM) bias correction method. The model domain covered the area from 90oE to 145oE and from 15oS to 40oN with a horizontal resolution of 25km. The QM bias correction processes were implemented by using the Vietnam Gridded precipitation dataset (VnGP) and the outputs of RegCM historical run in the period 1986-1995 and then validated for the period 1996-2005. Based on the statistical quantity of spatial correlation and intensity distributions, the QM method showed a significant improvement in rainfall compared to the non-bias correction method. The improvements both in time and space were recognized in all seasons and all climatic sub-regions of Vietnam. Moreover, not only the rainfall amount but also some extreme indices such as R10m, R20mm, R50m, CDD, CWD, R95pTOT, R99pTOT were much better after the correction. The results suggested that the QM correction method should be taken into practice for the projections of the future precipitation over Vietnam.
Brain MR image segmentation based on an improved active contour model
Meng, Xiangrui; Gu, Wenya; Zhang, Jianwei
2017-01-01
It is often a difficult task to accurately segment brain magnetic resonance (MR) images with intensity in-homogeneity and noise. This paper introduces a novel level set method for simultaneous brain MR image segmentation and intensity inhomogeneity correction. To reduce the effect of noise, novel anisotropic spatial information, which can preserve more details of edges and corners, is proposed by incorporating the inner relationships among the neighbor pixels. Then the proposed energy function uses the multivariate Student's t-distribution to fit the distribution of the intensities of each tissue. Furthermore, the proposed model utilizes Hidden Markov random fields to model the spatial correlation between neigh-boring pixels/voxels. The means of the multivariate Student's t-distribution can be adaptively estimated by multiplying a bias field to reduce the effect of intensity inhomogeneity. In the end, we reconstructed the energy function to be convex and calculated it by using the Split Bregman method, which allows our framework for random initialization, thereby allowing fully automated applications. Our method can obtain the final result in less than 1 second for 2D image with size 256 × 256 and less than 300 seconds for 3D image with size 256 × 256 × 171. The proposed method was compared to other state-of-the-art segmentation methods using both synthetic and clinical brain MR images and increased the accuracies of the results more than 3%. PMID:28854235
Lessio, Federico; Alma, Alberto
2006-04-01
The spatial distribution of the nymphs of Scaphoideus titanus Ball (Homoptera Cicadellidae), the vector of grapevine flavescence dorée (Candidatus Phytoplasma vitis, 16Sr-V), was studied by applying Taylor's power law. Studies were conducted from 2002 to 2005, in organic and conventional vineyards of Piedmont, northern Italy. Minimum sample size and fixed precision level stop lines were calculated to develop appropriate sampling plans. Model validation was performed, using independent field data, by means of Resampling Validation of Sample Plans (RVSP) resampling software. The nymphal distribution, analyzed via Taylor's power law, was aggregated, with b = 1.49. A sample of 32 plants was adequate at low pest densities with a precision level of D0 = 0.30; but for a more accurate estimate (D0 = 0.10), the required sample size needs to be 292 plants. Green's fixed precision level stop lines seem to be more suitable for field sampling: RVSP simulations of this sampling plan showed precision levels very close to the desired levels. However, at a prefixed precision level of 0.10, sampling would become too time-consuming, whereas a precision level of 0.25 is easily achievable. How these results could influence the correct application of the compulsory control of S. titanus and Flavescence dorée in Italy is discussed.
Distributed optical fiber vibration sensing using phase-generated carrier demodulation algorithm
NASA Astrophysics Data System (ADS)
Yu, Zhihua; Zhang, Qi; Zhang, Mingyu; Dai, Haolong; Zhang, Jingjing; Liu, Li; Zhang, Lijun; Jin, Xing; Wang, Gaifang; Qi, Guang
2018-05-01
A novel optical fiber-distributed vibration-sensing system is proposed, which is based on self-interference of Rayleigh backscattering with phase-generated carrier (PGC) demodulation algorithm. Pulsed lights are sent into the sensing fiber and the Rayleigh backscattering light from a certain position along the sensing fiber would interfere through an unbalanced Michelson interferometry to generate the interference light. An improved PGC demodulation algorithm is carried out to recover the phase information of the interference signal, which carries the sensing information. Three vibration events were applied simultaneously to different positions over 2000 m sensing fiber and demodulated correctly. The spatial resolution is 10 m, and the noise level of the Φ-OTDR system we proposed is about 10-3 rad/\\surd {Hz}, and the signal-to-noise ratio is about 30.34 dB.
Sample design effects in landscape genetics
Oyler-McCance, Sara J.; Fedy, Bradley C.; Landguth, Erin L.
2012-01-01
An important research gap in landscape genetics is the impact of different field sampling designs on the ability to detect the effects of landscape pattern on gene flow. We evaluated how five different sampling regimes (random, linear, systematic, cluster, and single study site) affected the probability of correctly identifying the generating landscape process of population structure. Sampling regimes were chosen to represent a suite of designs common in field studies. We used genetic data generated from a spatially-explicit, individual-based program and simulated gene flow in a continuous population across a landscape with gradual spatial changes in resistance to movement. Additionally, we evaluated the sampling regimes using realistic and obtainable number of loci (10 and 20), number of alleles per locus (5 and 10), number of individuals sampled (10-300), and generational time after the landscape was introduced (20 and 400). For a simulated continuously distributed species, we found that random, linear, and systematic sampling regimes performed well with high sample sizes (>200), levels of polymorphism (10 alleles per locus), and number of molecular markers (20). The cluster and single study site sampling regimes were not able to correctly identify the generating process under any conditions and thus, are not advisable strategies for scenarios similar to our simulations. Our research emphasizes the importance of sampling data at ecologically appropriate spatial and temporal scales and suggests careful consideration for sampling near landscape components that are likely to most influence the genetic structure of the species. In addition, simulating sampling designs a priori could help guide filed data collection efforts.
NASA Astrophysics Data System (ADS)
Harding, D. J.; Miuller, J. R.
2005-12-01
Modeling the kinematics of the 2004 Great Sumatra-Andaman earthquake is limited in the northern two-thirds of the rupture zone by a scarcity of near-rupture geodetic deformation measurements. Precisely repeated Ice, Cloud, and Land Elevation Satellite (ICESat) profiles across the Andaman and Nicobar Islands provide a means to more fully document the spatial pattern of surface vertical displacements and thus better constrain geomechanical modeling of the slip distribution. ICESat profiles that total ~45 km in length cross Car Nicobar, Kamorta, and Katchall in the Nicobar chain. Within the Andamans, the coverage includes ~350 km on North, Central, and South Andaman Islands along two NNE and NNW-trending profiles that provide elevations on both the east and west coasts of the island chain. Two profiles totaling ~80 km in length cross South Sentinel Island, and one profile ~10 km long crosses North Sentinel Island. With an average laser footprint spacing of 175 m, the total coverage provides over 2700 georeferenced surface elevations measurements for each operations period. Laser backscatter waveforms recorded for each footprint enable detection of forest canopy top and underlying ground elevations with decimeter vertical precision. Surface elevation change is determined from elevation profiles, acquired before and after the earthquake, that are repeated with a cross-track separation of less than 100 m by precision pointing of the ICESat spacecraft. Apparent elevation changes associated with cross-track offsets are corrected according to local slopes calculated from multiple post-earthquake repeated profiles. The surface deformation measurements recorded by ICESat are generally consistent with the spatial distribution of uplift predicted by a preliminary slip distribution model. To predict co-seismic surface deformation, we apply a slip distribution, derived from the released energy distribution computed by Ishii et al. (2005), as the displacement discontinuity boundary condition on the Sumatra-Andaman subduction interface fault. The direction of slip on the fault surface is derived from the slip directions computed by Tsai et al. (in review) for centroid moment tensor focal mechanisms spatially distributed along the rupture. The slip model will be refined to better correspond to the observed surface deformation as additional results from the ICESat profiles become available.
In situ detection of tree root distribution and biomass by multi-electrode resistivity imaging.
Amato, Mariana; Basso, Bruno; Celano, Giuseppe; Bitella, Giovanni; Morelli, Gianfranco; Rossi, Roberta
2008-10-01
Traditional methods for studying tree roots are destructive and labor intensive, but available nondestructive techniques are applicable only to small scale studies or are strongly limited by soil conditions and root size. Soil electrical resistivity measured by geoelectrical methods has the potential to detect belowground plant structures, but quantitative relationships of these measurements with root traits have not been assessed. We tested the ability of two-dimensional (2-D) DC resistivity tomography to detect the spatial variability of roots and to quantify their biomass in a tree stand. A high-resolution resistivity tomogram was generated along a 11.75 m transect under an Alnus glutinosa (L.) Gaertn. stand based on an alpha-Wenner configuration with 48 electrodes spaced 0.25 m apart. Data were processed by a 2-D finite-element inversion algorithm, and corrected for soil temperature. Data acquisition, inversion and imaging were completed in the field within 60 min. Root dry mass per unit soil volume (root mass density, RMD) was measured destructively on soil samples collected to a depth of 1.05 m. Soil sand, silt, clay and organic matter contents, electrical conductivity, water content and pH were measured on a subset of samples. The spatial pattern of soil resistivity closely matched the spatial distribution of RMD. Multiple linear regression showed that only RMD and soil water content were related to soil resistivity along the transect. Regression analysis of RMD against soil resistivity revealed a highly significant logistic relationship (n = 97), which was confirmed on a separate dataset (n = 67), showing that soil resistivity was quantitatively related to belowground tree root biomass. This relationship provides a basis for developing quick nondestructive methods for detecting root distribution and quantifying root biomass, as well as for optimizing sampling strategies for studying root-driven phenomena.
The Angular Three-Point Correlation Function in the Quasi-linear Regime
DOE Office of Scientific and Technical Information (OSTI.GOV)
Buchalter, Ari; Kamionkowski, Marc; Jaffe, Andrew H.
2000-02-10
We calculate the normalized angular three-point correlation function (3PCF), q, as well as the normalized angular skewness, s{sub 3}, assuming the small-angle approximation, for a biased mass distribution in flat and open cold dark matter (CDM) models with Gaussian initial conditions. The leading-order perturbative results incorporate the explicit dependence on the cosmological parameters, the shape of the CDM transfer function, the linear evolution of the power spectrum, the form of the assumed redshift distribution function, and linear and nonlinear biasing, which may be evolving. Results are presented for different redshift distributions, including that appropriate for the APM Galaxy Survey, asmore » well as for a survey with a mean redshift of z{approx_equal}1 (such as the VLA FIRST Survey). Qualitatively, many of the results found for s{sub 3} and q are similar to those obtained in a related treatment of the spatial skewness and 3PCF, such as a leading-order correction to the standard result for s{sub 3} in the case of nonlinear bias (as defined for unsmoothed density fields), and the sensitivity of the configuration dependence of q to both cosmological and biasing models. We show that since angular correlation functions (CFs) are sensitive to clustering over a range of redshifts, the various evolutionary dependences included in our predictions imply that measurements of q in a deep survey might better discriminate between models with different histories, such as evolving versus nonevolving bias, that can have similar spatial CFs at low redshift. Our calculations employ a derived equation, valid for open, closed, and flat models, to obtain the angular bispectrum from the spatial bispectrum in the small-angle approximation. (c) (c) 2000. The American Astronomical Society.« less
Falke, Jeffrey A.; Dunham, Jason B.; Jordan, Christopher E.; McNyset, Kris M.; Reeves, Gordon H.
2013-01-01
Processes that influence habitat selection in landscapes involve the interaction of habitat composition and configuration and are particularly important for species with complex life cycles. We assessed the relative influence of landscape spatial processes and local habitat characteristics on patterns in the distribution and abundance of spawning steelhead (Oncorhynchus mykiss), a threatened salmonid fish, across ~15,000 stream km in the John Day River basin, Oregon, USA. We used hurdle regression and a multi-model information theoretic approach to identify the relative importance of covariates representing key aspects of the steelhead life cycle (e.g., site access, spawning habitat quality, juvenile survival) at two spatial scales: within 2-km long survey reaches (local sites) and ecological neighborhoods (5 km) surrounding the local sites. Based on Akaike’s Information Criterion, models that included covariates describing ecological neighborhoods provided the best description of the distribution and abundance of steelhead spawning given the data. Among these covariates, our representation of offspring survival (growing-season-degree-days, °C) had the strongest effect size (7x) relative to other predictors. Predictive performances of model-averaged composite and neighborhood-only models were better than a site-only model based on both occurrence (percentage of sites correctly classified = 0.80±0.03 SD, 0.78±0.02 vs. 0.62±0.05, respectively) and counts (root mean square error = 3.37, 3.93 vs. 5.57, respectively). The importance of both temperature and stream flow for steelhead spawning suggest this species may be highly sensitive to impacts of land and water uses, and to projected climate impacts in the region and that landscape context, complementation, and connectivity will drive how this species responds to future environments.
NASA Astrophysics Data System (ADS)
Gyasi-Agyei, Yeboah
2018-01-01
This paper has established a link between the spatial structure of radar rainfall, which more robustly describes the spatial structure, and gauge rainfall for improved daily rainfield simulation conditioned on the limited gauged data for regions with or without radar records. A two-dimensional anisotropic exponential function that has parameters of major and minor axes lengths, and direction, is used to describe the correlogram (spatial structure) of daily rainfall in the Gaussian domain. The link is a copula-based joint distribution of the radar-derived correlogram parameters that uses the gauge-derived correlogram parameters and maximum daily temperature as covariates of the Box-Cox power exponential margins and Gumbel copula. While the gauge-derived, radar-derived and the copula-derived correlogram parameters reproduced the mean estimates similarly using leave-one-out cross-validation of ordinary kriging, the gauge-derived parameters yielded higher standard deviation (SD) of the Gaussian quantile which reflects uncertainty in over 90% of cases. However, the distribution of the SD generated by the radar-derived and the copula-derived parameters could not be distinguished. For the validation case, the percentage of cases of higher SD by the gauge-derived parameter sets decreased to 81.2% and 86.6% for the non-calibration and the calibration periods, respectively. It has been observed that 1% reduction in the Gaussian quantile SD can cause over 39% reduction in the SD of the median rainfall estimate, actual reduction being dependent on the distribution of rainfall of the day. Hence the main advantage of using the most correct radar correlogram parameters is to reduce the uncertainty associated with conditional simulations that rely on SD through kriging.
NASA Technical Reports Server (NTRS)
Ahmed, Kazi Farzan; Wang, Guiling; Silander, John; Wilson, Adam M.; Allen, Jenica M.; Horton, Radley; Anyah, Richard
2013-01-01
Statistical downscaling can be used to efficiently downscale a large number of General Circulation Model (GCM) outputs to a fine temporal and spatial scale. To facilitate regional impact assessments, this study statistically downscales (to 1/8deg spatial resolution) and corrects the bias of daily maximum and minimum temperature and daily precipitation data from six GCMs and four Regional Climate Models (RCMs) for the northeast United States (US) using the Statistical Downscaling and Bias Correction (SDBC) approach. Based on these downscaled data from multiple models, five extreme indices were analyzed for the future climate to quantify future changes of climate extremes. For a subset of models and indices, results based on raw and bias corrected model outputs for the present-day climate were compared with observations, which demonstrated that bias correction is important not only for GCM outputs, but also for RCM outputs. For future climate, bias correction led to a higher level of agreements among the models in predicting the magnitude and capturing the spatial pattern of the extreme climate indices. We found that the incorporation of dynamical downscaling as an intermediate step does not lead to considerable differences in the results of statistical downscaling for the study domain.
[Study on phase correction method of spatial heterodyne spectrometer].
Wang, Xin-Qiang; Ye, Song; Zhang, Li-Juan; Xiong, Wei
2013-05-01
Phase distortion exists in collected interferogram because of a variety of measure reasons when spatial heterodyne spectrometers are used in practice. So an improved phase correction method is presented. The phase curve of interferogram was obtained through Fourier inverse transform to extract single side transform spectrum, based on which, the phase distortions were attained by fitting phase slope, so were the phase correction functions, and the convolution was processed between transform spectrum and phase correction function to implement spectrum phase correction. The method was applied to phase correction of actually measured monochromatic spectrum and emulational water vapor spectrum. Experimental results show that the low-frequency false signals in monochromatic spectrum fringe would be eliminated effectively to increase the periodicity and the symmetry of interferogram, in addition when the continuous spectrum imposed phase error was corrected, the standard deviation between it and the original spectrum would be reduced form 0.47 to 0.20, and thus the accuracy of spectrum could be improved.
The topology of large Open Connectome networks for the human brain.
Gastner, Michael T; Ódor, Géza
2016-06-07
The structural human connectome (i.e. the network of fiber connections in the brain) can be analyzed at ever finer spatial resolution thanks to advances in neuroimaging. Here we analyze several large data sets for the human brain network made available by the Open Connectome Project. We apply statistical model selection to characterize the degree distributions of graphs containing up to nodes and edges. A three-parameter generalized Weibull (also known as a stretched exponential) distribution is a good fit to most of the observed degree distributions. For almost all networks, simple power laws cannot fit the data, but in some cases there is statistical support for power laws with an exponential cutoff. We also calculate the topological (graph) dimension D and the small-world coefficient σ of these networks. While σ suggests a small-world topology, we found that D < 4 showing that long-distance connections provide only a small correction to the topology of the embedding three-dimensional space.
The topology of large Open Connectome networks for the human brain
NASA Astrophysics Data System (ADS)
Gastner, Michael T.; Ódor, Géza
2016-06-01
The structural human connectome (i.e. the network of fiber connections in the brain) can be analyzed at ever finer spatial resolution thanks to advances in neuroimaging. Here we analyze several large data sets for the human brain network made available by the Open Connectome Project. We apply statistical model selection to characterize the degree distributions of graphs containing up to nodes and edges. A three-parameter generalized Weibull (also known as a stretched exponential) distribution is a good fit to most of the observed degree distributions. For almost all networks, simple power laws cannot fit the data, but in some cases there is statistical support for power laws with an exponential cutoff. We also calculate the topological (graph) dimension D and the small-world coefficient σ of these networks. While σ suggests a small-world topology, we found that D < 4 showing that long-distance connections provide only a small correction to the topology of the embedding three-dimensional space.
Cuypers, Eva; Flinders, Bryn; Boone, Carolien M; Bosman, Ingrid J; Lusthof, Klaas J; Van Asten, Arian C; Tytgat, Jan; Heeren, Ron M A
2016-03-15
Today, hair testing is considered to be the standard method for the detection of chronic drug abuse. Nevertheless, the differentiation between systemic exposure and external contamination remains a major challenge in the forensic interpretation of hair analysis. Nowadays, it is still impossible to directly show the difference between external contamination and use-related incorporation. Although the effects of washing procedures on the distribution of (incorporated) drugs in hair remain unknown, these decontamination procedures prior to hair analysis are considered to be indispensable in order to exclude external contamination. However, insights into the effect of decontamination protocols on levels and distribution of drugs incorporated in hair are essential to draw the correct forensic conclusions from hair analysis; we studied the consequences of these procedures on the spatial distribution of cocaine in hair using imaging mass spectrometry. Additionally, using metal-assisted secondary ion mass spectrometry, we are the first to directly show the difference between cocaine-contaminated and user hair without any prior washing procedure.
NASA Astrophysics Data System (ADS)
Liu, Yong-Yang; Xu, Yu-Liang; Liu, Zhong-Qiang; Li, Jing; Wang, Chun-Yang; Kong, Xiang-Mu
2018-07-01
Employing the correlation matrix technique, the spatial distribution of thermal energy in two-dimensional triangular lattices in equilibrium, interacting with linear springs, is studied. It is found that the spatial distribution of thermal energy varies with the included angle of the springs. In addition, the average thermal energy of the longer springs is lower. Springs with different included angle and length will lead to an inhomogeneous spatial distribution of thermal energy. This suggests that the spatial distribution of thermal energy is affected by the geometrical structure of the system: the more asymmetric the geometrical structure of the system is, the more inhomogeneous is the spatial distribution of thermal energy.
Wang, L L W; Perles, L A; Archambault, L; Sahoo, N; Mirkovic, D; Beddar, S
2013-01-01
The plastic scintillation detectors (PSD) have many advantages over other detectors in small field dosimetry due to its high spatial resolution, excellent water equivalence and instantaneous readout. However, in proton beams, the PSDs will undergo a quenching effect which makes the signal level reduced significantly when the detector is close to Bragg peak where the linear energy transfer (LET) for protons is very high. This study measures the quenching correction factor (QCF) for a PSD in clinical passive-scattering proton beams and investigates the feasibility of using PSDs in depth-dose measurements in proton beams. A polystyrene based PSD (BCF-12, ϕ0.5mm×4mm) was used to measure the depth-dose curves in a water phantom for monoenergetic unmodulated proton beams of nominal energies 100, 180 and 250 MeV. A Markus plane-parallel ion chamber was also used to get the dose distributions for the same proton beams. From these results, the QCF as a function of depth was derived for these proton beams. Next, the LET depth distributions for these proton beams were calculated by using the MCNPX Monte Carlo code, based on the experimentally validated nozzle models for these passive-scattering proton beams. Then the relationship between the QCF and the proton LET could be derived as an empirical formula. Finally, the obtained empirical formula was applied to the PSD measurements to get the corrected depth-dose curves and they were compared to the ion chamber measurements. A linear relationship between QCF and LET, i.e. Birks' formula, was obtained for the proton beams studied. The result is in agreement with the literature. The PSD measurements after the quenching corrections agree with ion chamber measurements within 5%. PSDs are good dosimeters for proton beam measurement if the quenching effect is corrected appropriately. PMID:23128412
NASA Astrophysics Data System (ADS)
Wang, L. L. W.; Perles, L. A.; Archambault, L.; Sahoo, N.; Mirkovic, D.; Beddar, S.
2012-12-01
Plastic scintillation detectors (PSDs) have many advantages over other detectors in small field dosimetry due to their high spatial resolution, excellent water equivalence and instantaneous readout. However, in proton beams, the PSDs undergo a quenching effect which makes the signal level reduced significantly when the detector is close to the Bragg peak where the linear energy transfer (LET) for protons is very high. This study measures the quenching correction factor (QCF) for a PSD in clinical passive-scattering proton beams and investigates the feasibility of using PSDs in depth-dose measurements in proton beams. A polystyrene-based PSD (BCF-12, ϕ0.5 mm × 4 mm) was used to measure the depth-dose curves in a water phantom for monoenergetic unmodulated proton beams of nominal energies 100, 180 and 250 MeV. A Markus plane-parallel ion chamber was also used to get the dose distributions for the same proton beams. From these results, the QCF as a function of depth was derived for these proton beams. Next, the LET depth distributions for these proton beams were calculated by using the MCNPX Monte Carlo code, based on the experimentally validated nozzle models for these passive-scattering proton beams. Then the relationship between the QCF and the proton LET could be derived as an empirical formula. Finally, the obtained empirical formula was applied to the PSD measurements to get the corrected depth-dose curves and they were compared to the ion chamber measurements. A linear relationship between the QCF and LET, i.e. Birks' formula, was obtained for the proton beams studied. The result is in agreement with the literature. The PSD measurements after the quenching corrections agree with ion chamber measurements within 5%. PSDs are good dosimeters for proton beam measurement if the quenching effect is corrected appropriately.
NASA Astrophysics Data System (ADS)
Lowry, D.; Fisher, R. E.; Zazzeri, G.; Lanoisellé, M.; France, J.; Allen, G.; Nisbet, E. G.
2017-12-01
Unlike the big open landscapes of many continents with large area sources dominated by one particular methane emission type that can be isotopically characterized by flight measurements and sampling, the complex patchwork of urban, fossil and agricultural methane sources across NW Europe require detailed ground surveys for characterization (Zazzeri et al., 2017). Here we outline the findings from multiple seasonal urban and rural measurement campaigns in the United Kingdom. These surveys aim to: 1) Assess source distribution and baseline in regions of planned fracking, and relate to on-site continuous baseline climatology. 2) Characterize spatial and seasonal differences in the isotopic signatures of the UNFCCC source categories, and 3) Assess the spatial validity of the 1 x 1 km UK inventory for large continuous emitters, proposed point sources, and seasonal / ephemeral emissions. The UK inventory suggests that 90% of methane emissions are from 3 source categories, ruminants, landfill and gas distribution. Bag sampling and GC-IRMS delta13C analysis shows that landfill gives a constant signature of -57 ±3 ‰ throughout the year. Fugitive gas emissions are consistent regionally depending on the North Sea supply regions feeding the network (-41 ± 2 ‰ in N England, -37 ± 2 ‰ in SE England). Ruminant, mostly cattle, emissions are far more complex as these spend winters in barns and summers in fields, but are essentially a mix of 2 end members, breath at -68 ±3 ‰ and manure at -51 ±3 ‰, resulting in broad summer field emission plumes of -64 ‰ and point winter barn emission plumes of -58 ‰. The inventory correctly locates emission hotspots from landfill, larger sewage treatment plants and gas compressor stations, giving a broad overview of emission distribution for regional model validation. Mobile surveys are adding an extra layer of detail to this which, combined with isotopic characterization, has identified spatial distribution of gas pipe leaks, some persisting since 2013 (Zazzeri et al., 2015), and seasonality and spatial variability of livestock emissions. Importantly existing significant gas leaks close to proposed fracking sites have been characterized so that any emissions to atmosphere with a different isotopic signature will be detected. Zazzeri, G., Atm. Env. 110, 151-162 (2015); Zazzeri, G., Sci. Rep. 7, 4854 (2017).
Dose and scatter characteristics of a novel cone beam CT system for musculoskeletal extremities
NASA Astrophysics Data System (ADS)
Zbijewski, W.; Sisniega, A.; Vaquero, J. J.; Muhit, A.; Packard, N.; Senn, R.; Yang, D.; Yorkston, J.; Carrino, J. A.; Siewerdsen, J. H.
2012-03-01
A novel cone-beam CT (CBCT) system has been developed with promising capabilities for musculoskeletal imaging (e.g., weight-bearing extremities and combined radiographic / volumetric imaging). The prototype system demonstrates diagnostic-quality imaging performance, while the compact geometry and short scan orbit raise new considerations for scatter management and dose characterization that challenge conventional methods. The compact geometry leads to elevated, heterogeneous x-ray scatter distributions - even for small anatomical sites (e.g., knee or wrist), and the short scan orbit results in a non-uniform dose distribution. These complex dose and scatter distributions were investigated via experimental measurements and GPU-accelerated Monte Carlo (MC) simulation. The combination provided a powerful basis for characterizing dose distributions in patient-specific anatomy, investigating the benefits of an antiscatter grid, and examining distinct contributions of coherent and incoherent scatter in artifact correction. Measurements with a 16 cm CTDI phantom show that the dose from the short-scan orbit (0.09 mGy/mAs at isocenter) varies from 0.16 to 0.05 mGy/mAs at various locations on the periphery (all obtained at 80 kVp). MC estimation agreed with dose measurements within 10-15%. Dose distribution in patient-specific anatomy was computed with MC, confirming such heterogeneity and highlighting the elevated energy deposition in bone (factor of ~5-10) compared to soft-tissue. Scatter-to-primary ratio (SPR) up to ~1.5-2 was evident in some regions of the knee. A 10:1 antiscatter grid was found earlier to result in significant improvement in soft-tissue imaging performance without increase in dose. The results of MC simulations elucidated the mechanism behind scatter reduction in the presence of a grid. A ~3-fold reduction in average SPR was found in the MC simulations; however, a linear grid was found to impart additional heterogeneity in the scatter distribution, mainly due to the increase in the contribution of coherent scatter with increased spatial variation. Scatter correction using MC-generated scatter distributions demonstrated significant improvement in cupping and streaks. Physical experimentation combined with GPU-accelerated MC simulation provided a sophisticated, yet practical approach in identifying low-dose acquisition techniques, optimizing scatter correction methods, and evaluating patientspecific dose.
Environmental boundaries as a mechanism for correcting and anchoring spatial maps
2016-01-01
Abstract Ubiquitous throughout the animal kingdom, path integration‐based navigation allows an animal to take a circuitous route out from a home base and using only self‐motion cues, calculate a direct vector back. Despite variation in an animal's running speed and direction, medial entorhinal grid cells fire in repeating place‐specific locations, pointing to the medial entorhinal circuit as a potential neural substrate for path integration‐based spatial navigation. Supporting this idea, grid cells appear to provide an environment‐independent metric representation of the animal's location in space and preserve their periodic firing structure even in complete darkness. However, a series of recent experiments indicate that spatially responsive medial entorhinal neurons depend on environmental cues in a more complex manner than previously proposed. While multiple types of landmarks may influence entorhinal spatial codes, environmental boundaries have emerged as salient landmarks that both correct error in entorhinal grid cells and bind internal spatial representations to the geometry of the external spatial world. The influence of boundaries on error correction and grid symmetry points to medial entorhinal border cells, which fire at a high rate only near environmental boundaries, as a potential neural substrate for landmark‐driven control of spatial codes. The influence of border cells on other entorhinal cell populations, such as grid cells, could depend on plasticity, raising the possibility that experience plays a critical role in determining how external cues influence internal spatial representations. PMID:26563618
Wang, Jian-Feng; Liu, Hong-Lin; Zhang, Shu-Qin; Yu, Xiang-Dong; Sun, Zhong-Zhou; Jin, Shang-Zhong; Zhang, Zai-Xuan
2013-04-01
Basic principles, development trends and applications status of distributed optical fiber Raman temperature sensor (DTS) are introduced. Performance parameters of DTS system include the sensing optical fiber length, temperature measurement uncertainty, spatial resolution and measurement time. These parameters have a certain correlation and it is difficult to improve them at the same time by single technology. So a variety of key techniques such as Raman amplification, pulse coding technique, Raman related dual-wavelength self-correction technique and embedding optical switching technique are researched to improve the performance of the DTS system. A 1 467 nm continuous laser is used as pump laser and the light source of DTS system (1 550 nm pulse laser) is amplified. When the length of sensing optical fiber is 50 km the Raman gain is about 17 dB. Raman gain can partially compensate the transmission loss of optical fiber, so that the sensing length can reach 50 km. In DTS system using pulse coding technique, pulse laser is coded by 211 bits loop encoder and correlation calculation is used to demodulate temperature. The encoded laser signal is related, whereas the noise is not relevant. So that signal-to-noise ratio (SNR) of DTS system can be improved significantly. The experiments are carried out in DTS system with single mode optical fiber and multimode optical fiber respectively. Temperature measurement uncertainty can all reach 1 degrees C. In DTS system using Raman related dual-wavelength self-correction technique, the wavelength difference of the two light sources must be one Raman frequency shift in optical fiber. For example, wavelength of the main laser is 1 550 nm and wavelength of the second laser must be 1 450 nm. Spatial resolution of DTS system is improved to 2 m by using dual-wavelength self-correction technique. Optical switch is embedded in DTS system, so that the temperature measurement channel multiply extended and the total length of the sensing optical fiber effectively extended. Optical fiber sensor network is composed.
NASA Technical Reports Server (NTRS)
Hanner, M. S.; Weinberg, J. L.; Beeson, D. E.; Sparrow, J. G.
1976-01-01
Sky maps made by the Pioneer 10 Imaging Photopolarimeter (IPP) at sun-spacecraft distances from 1 to 3 AU have been analyzed to derive the brightness of the zodiacal light near the ecliptic at elongations greater than 90 degrees. The change in zodiacal light brightness with heliocentric distance is compared with models of the spatial distribution of the dust. Use of background starlight brightnesses derived from IPP measurements beyond the asteroid belt, where the zodiacal light is not detected, and, especially, use of a corrected calibration lead to considerably lower values for zodiacal light than those reported by us previously.
Monitoring gypsy moth defoliation by applying change detection techniques to Landsat imagery
NASA Technical Reports Server (NTRS)
Williams, D. L.; Stauffer, M. L.
1978-01-01
The overall objective of a research effort at NASA's Goddard Space Flight Center is to develop and evaluate digital image processing techniques that will facilitate the assessment of the intensity and spatial distribution of forest insect damage in Northeastern U.S. forests using remotely sensed data from Landsats 1, 2 and C. Automated change detection techniques are presently being investigated as a method of isolating the areas of change in the forest canopy resulting from pest outbreaks. In order to follow the change detection approach, Landsat scene correction and overlay capabilities are utilized to provide multispectral/multitemporal image files of 'defoliation' and 'nondefoliation' forest stand conditions.
Duffaut Espinosa, L A; Posadas, A N; Carbajal, M; Quiroz, R
2017-01-01
In this paper, a multifractal downscaling technique is applied to adequately transformed and lag corrected normalized difference vegetation index (NDVI) in order to obtain daily estimates of rainfall in an area of the Peruvian Andean high plateau. This downscaling procedure is temporal in nature since the original NDVI information is provided at an irregular temporal sampling period between 8 and 11 days, and the desired final scale is 1 day. The spatial resolution of approximately 1 km remains the same throughout the downscaling process. The results were validated against on-site measurements of meteorological stations distributed in the area under study.
Posadas, A. N.; Carbajal, M.; Quiroz, R.
2017-01-01
In this paper, a multifractal downscaling technique is applied to adequately transformed and lag corrected normalized difference vegetation index (NDVI) in order to obtain daily estimates of rainfall in an area of the Peruvian Andean high plateau. This downscaling procedure is temporal in nature since the original NDVI information is provided at an irregular temporal sampling period between 8 and 11 days, and the desired final scale is 1 day. The spatial resolution of approximately 1 km remains the same throughout the downscaling process. The results were validated against on-site measurements of meteorological stations distributed in the area under study. PMID:28125607
Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling.
Yu, Ze; Lin, Peng; Xiao, Peng; Kang, Lihong; Li, Chunsheng
2016-07-14
Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range and azimuth. As a result, efficient and precise imaging becomes difficult. This paper analyzes and models spatial variance for GEO SAR in the time and frequency domains. A novel algorithm for GEO SAR imaging with a resolution of 2 m in both the ground cross-range and range directions is proposed, which is composed of five steps. The first is to eliminate linear azimuth variance through the first azimuth time scaling. The second is to achieve RCM correction and range compression. The third is to correct residual azimuth variance by the second azimuth time-frequency scaling. The fourth and final steps are to accomplish azimuth focusing and correct geometric distortion. The most important innovation of this algorithm is implementation of the time-frequency scaling to correct high-order azimuth variance. As demonstrated by simulation results, this algorithm can accomplish GEO SAR imaging with good and uniform imaging quality over the entire swath.
Correcting Spatial Variance of RCM for GEO SAR Imaging Based on Time-Frequency Scaling
Yu, Ze; Lin, Peng; Xiao, Peng; Kang, Lihong; Li, Chunsheng
2016-01-01
Compared with low-Earth orbit synthetic aperture radar (SAR), a geosynchronous (GEO) SAR can have a shorter revisit period and vaster coverage. However, relative motion between this SAR and targets is more complicated, which makes range cell migration (RCM) spatially variant along both range and azimuth. As a result, efficient and precise imaging becomes difficult. This paper analyzes and models spatial variance for GEO SAR in the time and frequency domains. A novel algorithm for GEO SAR imaging with a resolution of 2 m in both the ground cross-range and range directions is proposed, which is composed of five steps. The first is to eliminate linear azimuth variance through the first azimuth time scaling. The second is to achieve RCM correction and range compression. The third is to correct residual azimuth variance by the second azimuth time-frequency scaling. The fourth and final steps are to accomplish azimuth focusing and correct geometric distortion. The most important innovation of this algorithm is implementation of the time-frequency scaling to correct high-order azimuth variance. As demonstrated by simulation results, this algorithm can accomplish GEO SAR imaging with good and uniform imaging quality over the entire swath. PMID:27428974
Inui, Yoshitaka; Ichihara, Takashi; Uno, Masaki; Ishiguro, Masanobu; Ito, Kengo; Kato, Katsuhiko; Sakuma, Hajime; Okazawa, Hidehiko; Toyama, Hiroshi
2018-06-01
Statistical image analysis of brain SPECT images has improved diagnostic accuracy for brain disorders. However, the results of statistical analysis vary depending on the institution even when they use a common normal database (NDB), due to different intrinsic spatial resolutions or correction methods. The present study aimed to evaluate the correction of spatial resolution differences between equipment and examine the differences in skull bone attenuation to construct a common NDB for use in multicenter settings. The proposed acquisition and processing protocols were those routinely used at each participating center with additional triple energy window (TEW) scatter correction (SC) and computed tomography (CT) based attenuation correction (CTAC). A multicenter phantom study was conducted on six imaging systems in five centers, with either single photon emission computed tomography (SPECT) or SPECT/CT, and two brain phantoms. The gray/white matter I-123 activity ratio in the brain phantoms was 4, and they were enclosed in either an artificial adult male skull, 1300 Hounsfield units (HU), a female skull, 850 HU, or an acrylic cover. The cut-off frequency of the Butterworth filters was adjusted so that the spatial resolution was unified to a 17.9 mm full width at half maximum (FWHM), that of the lowest resolution system. The gray-to-white matter count ratios were measured from SPECT images and compared with the actual activity ratio. In addition, mean, standard deviation and coefficient of variation images were calculated after normalization and anatomical standardization to evaluate the variability of the NDB. The gray-to-white matter count ratio error without SC and attenuation correction (AC) was significantly larger for higher bone densities (p < 0.05). The count ratio error with TEW and CTAC was approximately 5% regardless of bone density. After adjustment of the spatial resolution in the SPECT images, the variability of the NDB decreased and was comparable to that of the NDB without correction. The proposed protocol showed potential for constructing an appropriate common NDB from SPECT images with SC, AC and spatial resolution compensation.
NASA Astrophysics Data System (ADS)
Krot, Yury; Beliaev, Boris; Katkovsky, Leonid
2016-10-01
Aerospace Research Department of the Institute of Applied Physical Problems at Belarusian State University has developed a prototype of the optical payload intended for a space experiment on the ISS board. The prototype includes four optical modules for the night glows observation, in particular spatial-brightness and spectral characteristics in the altitude range of 80-320 km. Objects of the interest are emitting top layers of the atmosphere including exited OH radicals, atomic and molecular oxygen and sodium layers. The goal of the space experiment is a research of night glows over different regions of the Earth and a connection with natural disasters like earthquakes, cyclones, etc. Two optical modules for spatial distribution of atomic oxygen layers along the altitude consist of input lenses, spectral interferential filters and line CCD detectors. The optical module for registration of exited OH radical emissions is formed from CCD array spectrometer. The payload includes also a panchromatic (400-900 nm) high sensitive imaging camera for observing of the glows general picture. The optical modules of the prototype have been tested and general optical characteristics were determined in laboratory conditions. A solution of an astigmatism reducing of a concave diffraction grating and a method of the second diffraction order correction were applied and improved spectrometer's optical characteristics. Laboratory equipment and software were developed to imitate a dynamic scene of the night glows in laboratory conditions including an imitation of linear spectra and the spatial distribution of emissions.
Niger-wide assessment of in situ sorghum genetic diversity with microsatellite markers.
Deu, M; Sagnard, F; Chantereau, J; Calatayud, C; Hérault, D; Mariac, C; Pham, J-L; Vigouroux, Y; Kapran, I; Traore, P S; Mamadou, A; Gerard, B; Ndjeunga, J; Bezançon, G
2008-05-01
Understanding the geographical, environmental and social patterns of genetic diversity on different spatial scales is key to the sustainable in situ management of genetic resources. However, few surveys have been conducted on crop genetic diversity using exhaustive in situ germplasm collections on a country scale and such data are missing for sorghum in sub-Saharan Africa, its centre of origin. We report here a genetic analysis of 484 sorghum varieties collected in 79 villages evenly distributed across Niger, using 28 microsatellite markers. We found a high level of SSR diversity in Niger. Diversity varied between eastern and western Niger, and allelic richness was lower in the eastern part of the country. Genetic differentiation between botanical races was the first structuring factor (Fst = 0.19), but the geographical distribution and the ethnic group to which farmers belonged were also significantly associated with genetic diversity partitioning. Gene pools are poorly differentiated among climatic zones. The geographical situation of Niger, where typical western African (guinea), central African (caudatum) and eastern Sahelian African (durra) sorghum races converge, explained the high observed genetic diversity and was responsible for the interactions among the ethnic, geographical and botanical structure revealed in our study. After correcting for the structure of botanical races, spatial correlation of genetic diversity was still detected within 100 km, which may hint at limited seed exchanges between farmers. Sorghum domestication history, in relation to the spatial organisation of human societies, is therefore key information for sorghum in situ conservation programs in sub-Saharan Africa.
Spatial distribution of traffic in a cellular mobile data network
NASA Astrophysics Data System (ADS)
Linnartz, J. P. M. G.
1987-02-01
The use of integral transforms of the probability density function for the received power to analyze the relation between the spatial distributions of offered and throughout packet traffic in a mobile radio network with Rayleigh fading channels and ALOHA multiple access was assessed. A method to obtain the spatial distribution of throughput traffic from a prescribed spatial distribution of offered traffic is presented. Incoherent and coherent addition of interference signals is considered. The channel behavior for heavy traffic loads is studied. In both the incoherent and coherent case, the spatial distribution of offered traffic required to ensure a prescribed spatially uniform throughput is synthesized numerically.
Monte Carlo calculations of positron emitter yields in proton radiotherapy.
Seravalli, E; Robert, C; Bauer, J; Stichelbaut, F; Kurz, C; Smeets, J; Van Ngoc Ty, C; Schaart, D R; Buvat, I; Parodi, K; Verhaegen, F
2012-03-21
Positron emission tomography (PET) is a promising tool for monitoring the three-dimensional dose distribution in charged particle radiotherapy. PET imaging during or shortly after proton treatment is based on the detection of annihilation photons following the ß(+)-decay of radionuclides resulting from nuclear reactions in the irradiated tissue. Therapy monitoring is achieved by comparing the measured spatial distribution of irradiation-induced ß(+)-activity with the predicted distribution based on the treatment plan. The accuracy of the calculated distribution depends on the correctness of the computational models, implemented in the employed Monte Carlo (MC) codes that describe the interactions of the charged particle beam with matter and the production of radionuclides and secondary particles. However, no well-established theoretical models exist for predicting the nuclear interactions and so phenomenological models are typically used based on parameters derived from experimental data. Unfortunately, the experimental data presently available are insufficient to validate such phenomenological hadronic interaction models. Hence, a comparison among the models used by the different MC packages is desirable. In this work, starting from a common geometry, we compare the performances of MCNPX, GATE and PHITS MC codes in predicting the amount and spatial distribution of proton-induced activity, at therapeutic energies, to the already experimentally validated PET modelling based on the FLUKA MC code. In particular, we show how the amount of ß(+)-emitters produced in tissue-like media depends on the physics model and cross-sectional data used to describe the proton nuclear interactions, thus calling for future experimental campaigns aiming at supporting improvements of MC modelling for clinical application of PET monitoring. © 2012 Institute of Physics and Engineering in Medicine
A novel method for correcting scanline-observational bias of discontinuity orientation
Huang, Lei; Tang, Huiming; Tan, Qinwen; Wang, Dingjian; Wang, Liangqing; Ez Eldin, Mutasim A. M.; Li, Changdong; Wu, Qiong
2016-01-01
Scanline observation is known to introduce an angular bias into the probability distribution of orientation in three-dimensional space. In this paper, numerical solutions expressing the functional relationship between the scanline-observational distribution (in one-dimensional space) and the inherent distribution (in three-dimensional space) are derived using probability theory and calculus under the independence hypothesis of dip direction and dip angle. Based on these solutions, a novel method for obtaining the inherent distribution (also for correcting the bias) is proposed, an approach which includes two procedures: 1) Correcting the cumulative probabilities of orientation according to the solutions, and 2) Determining the distribution of the corrected orientations using approximation methods such as the one-sample Kolmogorov-Smirnov test. The inherent distribution corrected by the proposed method can be used for discrete fracture network (DFN) modelling, which is applied to such areas as rockmass stability evaluation, rockmass permeability analysis, rockmass quality calculation and other related fields. To maximize the correction capacity of the proposed method, the observed sample size is suggested through effectiveness tests for different distribution types, dispersions and sample sizes. The performance of the proposed method and the comparison of its correction capacity with existing methods are illustrated with two case studies. PMID:26961249
NASA Astrophysics Data System (ADS)
Pietrzyk, Mariusz W.; Manning, David; Donovan, Tim; Dix, Alan
2010-02-01
Aim: To investigate the impact on visual sampling strategy and pulmonary nodule recognition of image-based properties of background locations in dwelled regions where the first overt decision was made. . Background: Recent studies in mammography show that the first overt decision (TP or FP) has an influence on further image reading including the correctness of the following decisions. Furthermore, the correlation between the spatial frequency properties of the local background following decision sites and the first decision correctness has been reported. Methods: Subjects with different radiological experience were eye tracked during detection of pulmonary nodules from PA chest radiographs. Number of outcomes and the overall quality of performance are analysed in terms of the cases where correct or incorrect decisions were made. JAFROC methodology is applied. The spatial frequency properties of selected local backgrounds related to a certain decisions were studied. ANOVA was used to compare the logarithmic values of energy carried by non redundant stationary wavelet packet coefficients. Results: A strong correlation has been found between the number of TP as a first decision and the JAFROC score (r = 0.74). The number of FP as a first decision was found negatively correlated with JAFROC (r = -0.75). Moreover, the differential spatial frequency profiles outcomes depend on the first choice correctness.
Ohyu, Shigeharu; Okamoto, Yoshiwo; Kuriki, Shinya
2002-06-01
A novel magnetocardiographic inverse method for reconstructing the action potential amplitude (APA) and the activation time (AT) on the ventricular myocardium is proposed. This method is based on the propagated excitation model, in which the excitation is propagated through the ventricle with nonuniform height of action potential. Assumption of stepwise waveform on the transmembrane potential was introduced in the model. Spatial gradient of transmembrane potential, which is defined by APA and AT distributed in the ventricular wall, is used for the computation of a current source distribution. Based on this source model, the distributions of APA and AT are inversely reconstructed from the QRS interval of magnetocardiogram (MCG) utilizing a maximum a posteriori approach. The proposed reconstruction method was tested through computer simulations. Stability of the methods with respect to measurement noise was demonstrated. When reference APA was provided as a uniform distribution, root-mean-square errors of estimated APA were below 10 mV for MCG signal-to-noise ratios greater than, or equal to, 20 dB. Low-amplitude regions located at several sites in reference APA distributions were correctly reproduced in reconstructed APA distributions. The goal of our study is to develop a method for detecting myocardial ischemia through the depression of reconstructed APA distributions.
The magnetisation distribution of the Ising model - a new approach
NASA Astrophysics Data System (ADS)
Hakan Lundow, Per; Rosengren, Anders
2010-03-01
A completely new approach to the Ising model in 1 to 5 dimensions is developed. We employ a generalisation of the binomial coefficients to describe the magnetisation distributions of the Ising model. For the complete graph this distribution is exact. For simple lattices of dimensions d=1 and d=5 the magnetisation distributions are remarkably well-fitted by the generalized binomial distributions. For d=4 we are only slightly less successful, while for d=2,3 we see some deviations (with exceptions!) between the generalized binomial and the Ising distribution. The results speak in favour of the generalized binomial distribution's correctness regarding their general behaviour in comparison to the Ising model. A theoretical analysis of the distribution's moments also lends support their being correct asymptotically, including the logarithmic corrections in d=4. The full extent to which they correctly model the Ising distribution, and for which graph families, is not settled though.
Winter Distribution of On-road NO2 Concentration in Hong Kong
NASA Astrophysics Data System (ADS)
Zhu, Y.; Chan, K. L.; Boll, J.; Schütt, A. M. N.; Lipkowitsch, I.; Wenig, M.
2017-12-01
In this study, we investigated the spatial distribution of on road NO2 concentration using Cavity-Enhanced Differential Optical Absorption Spectroscopy (DOAS). We performed two measurement campaigns in winter 2010 and 2017. Air pollution is a severe problem for many big cities, especially in Asia. Traffic emission is the primary source of urban pollutants. As Hong Kong is one of the most densely populated cities in the world, many inhabitants are exposed to accumulated pollutants in street canyons. Our mobile measurements were performed for a week in December, 2010 and March, 2017. Additionally, long term air pollution data measured by a long-path DOAS (LP-DOAS) and the Environment Protection Department (EPD) air quality monitoring network were used to investigate the long term trend and seasonal variations of atmospheric NO2 in Hong Kong.The experiment setup and preliminary results of mobile measurements are presented. The measurements were performed along a fixed route which covers most of the urban area. We assembled a NO2 concentration map 2 to 3 times per day in order to cover both morning and evening rush hours. In order to construct a consistent map, we use coinciding LP-DOAS NO2 data to correct for the diurnal cycle. Furthermore, the spatial and temporal distribution of NO2 changes with the day of the week. Traffic load is highly dependent on human activities which typically fall into a 7 days cycle. Therefore, we have analyzed the weekly pattern of on road NO2 distribution to see the differences between anthropogenic emissions during weekdays and weekend.
Songhurst, Anna; Coulson, Tim
2014-03-01
Few universal trends in spatial patterns of wildlife crop-raiding have been found. Variations in wildlife ecology and movements, and human spatial use have been identified as causes of this apparent unpredictability. However, varying spatial patterns of spatial autocorrelation (SA) in human-wildlife conflict (HWC) data could also contribute. We explicitly explore the effects of SA on wildlife crop-raiding data in order to facilitate the design of future HWC studies. We conducted a comparative survey of raided and nonraided fields to determine key drivers of crop-raiding. Data were subsampled at different spatial scales to select independent raiding data points. The model derived from all data was fitted to subsample data sets. Model parameters from these models were compared to determine the effect of SA. Most methods used to account for SA in data attempt to correct for the change in P-values; yet, by subsampling data at broader spatial scales, we identified changes in regression estimates. We consequently advocate reporting both model parameters across a range of spatial scales to help biological interpretation. Patterns of SA vary spatially in our crop-raiding data. Spatial distribution of fields should therefore be considered when choosing the spatial scale for analyses of HWC studies. Robust key drivers of elephant crop-raiding included raiding history of a field and distance of field to a main elephant pathway. Understanding spatial patterns and determining reliable socio-ecological drivers of wildlife crop-raiding is paramount for designing mitigation and land-use planning strategies to reduce HWC. Spatial patterns of HWC are complex, determined by multiple factors acting at more than one scale; therefore, studies need to be designed with an understanding of the effects of SA. Our methods are accessible to a variety of practitioners to assess the effects of SA, thereby improving the reliability of conservation management actions.
48 CFR 1846.672-4 - Correction instructions.
Code of Federal Regulations, 2010 CFR
2010-10-01
... 48 Federal Acquisition Regulations System 6 2010-10-01 2010-10-01 true Correction instructions. 1846.672-4 Section 1846.672-4 Federal Acquisition Regulations System NATIONAL AERONAUTICS AND SPACE... distribution, it shall be revised by correcting the original master and distributing the corrected form. The...
NASA Astrophysics Data System (ADS)
Lorente-Plazas, Raquel; Hacker, Josua P.; Collins, Nancy; Lee, Jared A.
2017-04-01
The impact of assimilating surface observations has been shown in several publications, for improving weather prediction inside of the boundary layer as well as the flow aloft. However, the assimilation of surface observations is often far from optimal due to the presence of both model and observation biases. The sources of these biases can be diverse: an instrumental offset, errors associated to the comparison of point-based observations and grid-cell average, etc. To overcome this challenge, a method was developed using the ensemble Kalman filter. The approach consists on representing each observation bias as a parameter. These bias parameters are added to the forward operator and they extend the state vector. As opposed to the observation bias estimation approaches most common in operational systems (e.g. for satellite radiances), the state vector and parameters are simultaneously updated by applying the Kalman filter equations to the augmented state. The method to estimate and correct the observation bias is evaluated using observing system simulation experiments (OSSEs) with the Weather Research and Forecasting (WRF) model. OSSEs are constructed for the conventional observation network including radiosondes, aircraft observations, atmospheric motion vectors, and surface observations. Three different kinds of biases are added to 2-meter temperature for synthetic METARs. From the simplest to more sophisticated, imposed biases are: (1) a spatially invariant bias, (2) a spatially varying bias proportional to topographic height differences between the model and the observations, and (3) bias that is proportional to the temperature. The target region characterized by complex terrain is the western U.S. on a domain with 30-km grid spacing. Observations are assimilated every 3 hours using an 80-member ensemble during September 2012. Results demonstrate that the approach is able to estimate and correct the bias when it is spatially invariant (experiment 1). More complex bias structure in experiments (2) and (3) are more difficult to estimate, but still possible. Estimated the parameter in experiments with unbiased observations results in spatial and temporal parameter variability about zero, and establishes a threshold on the accuracy of the parameter in further experiments. When the observations are biased, the mean parameter value is close to the true bias, but temporal and spatial variability in the parameter estimates is similar to the parameters used when estimating a zero bias in the observations. The distributions are related to other errors in the forecasts, indicating that the parameters are absorbing some of the forecast error from other sources. In this presentation we elucidate the reasons for the resulting parameter estimates, and their variability.
GASS: the Parkes Galactic all-sky survey. II. Stray-radiation correction and second data release
NASA Astrophysics Data System (ADS)
Kalberla, P. M. W.; McClure-Griffiths, N. M.; Pisano, D. J.; Calabretta, M. R.; Ford, H. Alyson; Lockman, F. J.; Staveley-Smith, L.; Kerp, J.; Winkel, B.; Murphy, T.; Newton-McGee, K.
2010-10-01
Context. The Parkes Galactic all-sky survey (GASS) is a survey of Galactic atomic hydrogen (H i) emission in the southern sky observed with the Parkes 64-m Radio Telescope. The first data release was published by McClure-Griffiths et al. (2009). Aims: We remove instrumental effects that affect the GASS and present the second data release. Methods: We calculate the stray-radiation by convolving the all-sky response of the Parkes antenna with the brightness temperature distribution from the Leiden/Argentine/Bonn (LAB) all sky 21-cm line survey, with major contributions from the 30-m dish of the Instituto Argentino de Radioastronomía (IAR) in the southern sky. Remaining instrumental baselines are corrected using the LAB data for a first guess of emission-free baseline regions. Radio frequency interference is removed by median filtering. Results: After applying these corrections to the GASS we find an excellent agreement with the Leiden/Argentine/Bonn (LAB) survey. The GASS is the highest spatial resolution, most sensitive, and is currently the most accurate H i survey of the Galactic H i emission in the southern sky. We provide a web interface for generation and download of FITS cubes.
J. Rojas-Sandoval; E. J. Melendez-Ackerman; NO-VALUE
2013-01-01
Aims The spatial distribution of biotic and abiotic factors may play a dominant role in determining the distribution and abundance of plants in arid and semiarid environments. In this study, we evaluated how spatial patterns of microhabitat variables and the degree of spatial dependence of these variables influence the distribution and abundance of the endangered...
[Spatial distribution pattern of Chilo suppressalis analyzed by classical method and geostatistics].
Yuan, Zheming; Fu, Wei; Li, Fangyi
2004-04-01
Two original samples of Chilo suppressalis and their grid, random and sequence samples were analyzed by classical method and geostatistics to characterize the spatial distribution pattern of C. suppressalis. The limitations of spatial distribution analysis with classical method, especially influenced by the original position of grid, were summarized rather completely. On the contrary, geostatistics characterized well the spatial distribution pattern, congregation intensity and spatial heterogeneity of C. suppressalis. According to geostatistics, the population was up to Poisson distribution in low density. As for higher density population, its distribution was up to aggregative, and the aggregation intensity and dependence range were 0.1056 and 193 cm, respectively. Spatial heterogeneity was also found in the higher density population. Its spatial correlativity in line direction was more closely than that in row direction, and the dependence ranges in line and row direction were 115 and 264 cm, respectively.
Importance of spatial autocorrelation in modeling bird distributions at a continental scale
Bahn, V.; O'Connor, R.J.; Krohn, W.B.
2006-01-01
Spatial autocorrelation in species' distributions has been recognized as inflating the probability of a type I error in hypotheses tests, causing biases in variable selection, and violating the assumption of independence of error terms in models such as correlation or regression. However, it remains unclear whether these problems occur at all spatial resolutions and extents, and under which conditions spatially explicit modeling techniques are superior. Our goal was to determine whether spatial models were superior at large extents and across many different species. In addition, we investigated the importance of purely spatial effects in distribution patterns relative to the variation that could be explained through environmental conditions. We studied distribution patterns of 108 bird species in the conterminous United States using ten years of data from the Breeding Bird Survey. We compared the performance of spatially explicit regression models with non-spatial regression models using Akaike's information criterion. In addition, we partitioned the variance in species distributions into an environmental, a pure spatial and a shared component. The spatially-explicit conditional autoregressive regression models strongly outperformed the ordinary least squares regression models. In addition, partialling out the spatial component underlying the species' distributions showed that an average of 17% of the explained variation could be attributed to purely spatial effects independent of the spatial autocorrelation induced by the underlying environmental variables. We concluded that location in the range and neighborhood play an important role in the distribution of species. Spatially explicit models are expected to yield better predictions especially for mobile species such as birds, even in coarse-grained models with a large extent. ?? Ecography.
Pediatric and adolescent applications of the Taylor Spatial Frame.
Paloski, Michael; Taylor, Benjamin C; Iobst, Christopher; Pugh, Kevin J
2012-06-01
Limb deformity can occur in the pediatric and adolescent populations from multiple etiologies: congenital, traumatic, posttraumatic sequelae, oncologic, and infection. Correcting these deformities is important for many reasons. Ilizarov popularized external fixation to accomplish this task. Taylor expanded on this by designing an external fixator in 1994 with 6 telescoping struts that can be sequentially manipulated to achieve multiaxial correction of deformity without the need for hinges or operative frame alterations. This frame can be used to correct deformities in children and has shown good anatomic correction with minimal morbidity. The nature of the construct and length of treatment affects psychosocial factors that the surgeon and family must be aware of prior to treatment. An understanding of applications of the Taylor Spatial Frame gives orthopedic surgeons an extra tool to correct simple and complex deformities in pediatric and adolescent patients. Copyright 2012, SLACK Incorporated.
Do large-scale inhomogeneities explain away dark energy?
NASA Astrophysics Data System (ADS)
Geshnizjani, Ghazal; Chung, Daniel J.; Afshordi, Niayesh
2005-07-01
Recently, new arguments [E. Barausse, S. Matarrese, and A. Riotto, Phys. Rev. D 71, 063537 (2005)., PRVDAQ, 0556-2821, 10.1103/PhysRevD.71.063537][
NASA Astrophysics Data System (ADS)
Gopalan, Giri; Hrafnkelsson, Birgir; Aðalgeirsdóttir, Guðfinna; Jarosch, Alexander H.; Pálsson, Finnur
2018-03-01
Bayesian hierarchical modeling can assist the study of glacial dynamics and ice flow properties. This approach will allow glaciologists to make fully probabilistic predictions for the thickness of a glacier at unobserved spatio-temporal coordinates, and it will also allow for the derivation of posterior probability distributions for key physical parameters such as ice viscosity and basal sliding. The goal of this paper is to develop a proof of concept for a Bayesian hierarchical model constructed, which uses exact analytical solutions for the shallow ice approximation (SIA) introduced by Bueler et al. (2005). A suite of test simulations utilizing these exact solutions suggests that this approach is able to adequately model numerical errors and produce useful physical parameter posterior distributions and predictions. A byproduct of the development of the Bayesian hierarchical model is the derivation of a novel finite difference method for solving the SIA partial differential equation (PDE). An additional novelty of this work is the correction of numerical errors induced through a numerical solution using a statistical model. This error correcting process models numerical errors that accumulate forward in time and spatial variation of numerical errors between the dome, interior, and margin of a glacier.
Hassan, Atef; Letts, Merv
2012-01-01
Neglected or inadequately treated rigid congenitally deformed feet in older children are a nightmarish challenge for the child, the parents, and the orthopaedic surgeon. Because of the multiplicity of spatial deformities exhibited by these feet and legs, it was hypothesized that correction using the Taylor spatial frame (TSF) would decrease morbidity, facilitate correction, and minimize treatment time in children from remote regions with extremely rigid deformed feet. Recent experience with the management of 11 such feet (Dimeglio type IV) in 9 children with an average age of 9.2 years using the TSF has been gratifying. Six children had associated leg length discrepancy, which was corrected by concomitant tibial lengthening. All feet underwent soft tissue releases, whereas forefoot and/or hindfoot osteotomies were performed in 7 feet. All children attained plantigrade, functional feet, and were fully ambulatory and capable of wearing normal footwear. Complications were minor consisting of pin tract infections, residual metatarsus varus in 3, and wound dehiscence in 1. There were no neurovascular events. This was attributed to the slower 3 plane correction using the TSF technique as well as the elimination of the need for plaster immobilization thus allowing direct monitoring of the foot and limb. The rigid foot deformity in the older child can be safely and effectively corrected with the aid of the TSF, which facilitates a 3 plane correction and concomitant limb lengthening.
Li, Haoting; Chen, Rongqing; Xu, Canhua; Liu, Benyuan; Tang, Mengxing; Yang, Lin; Dong, Xiuzhen; Fu, Feng
2017-08-21
Dynamic brain electrical impedance tomography (EIT) is a promising technique for continuously monitoring the development of cerebral injury. While there are many reconstruction algorithms available for brain EIT, there is still a lack of study to compare their performance in the context of dynamic brain monitoring. To address this problem, we develop a framework for evaluating different current algorithms with their ability to correctly identify small intracranial conductivity changes. Firstly, a simulation 3D head phantom with realistic layered structure and impedance distribution is developed. Next several reconstructing algorithms, such as back projection (BP), damped least-square (DLS), Bayesian, split Bregman (SB) and GREIT are introduced. We investigate their temporal response, noise performance, location and shape error with respect to different noise levels on the simulation phantom. The results show that the SB algorithm demonstrates superior performance in reducing image error. To further improve the location accuracy, we optimize SB by incorporating the brain structure-based conductivity distribution priors, in which differences of the conductivities between different brain tissues and the inhomogeneous conductivity distribution of the skull are considered. We compare this novel algorithm (called SB-IBCD) with SB and DLS using anatomically correct head shaped phantoms with spatial varying skull conductivity. Main results and Significance: The results showed that SB-IBCD is the most effective in unveiling small intracranial conductivity changes, where it can reduce the image error by an average of 30.0% compared to DLS.
NASA Technical Reports Server (NTRS)
Haralick, R. H. (Principal Investigator); Bosley, R. J.
1974-01-01
The author has identified the following significant results. A procedure was developed to extract cross-band textural features from ERTS MSS imagery. Evolving from a single image texture extraction procedure which uses spatial dependence matrices to measure relative co-occurrence of nearest neighbor grey tones, the cross-band texture procedure uses the distribution of neighboring grey tone N-tuple differences to measure the spatial interrelationships, or co-occurrences, of the grey tone N-tuples present in a texture pattern. In both procedures, texture is characterized in such a way as to be invariant under linear grey tone transformations. However, the cross-band procedure complements the single image procedure by extracting texture information and spectral information contained in ERTS multi-images. Classification experiments show that when used alone, without spectral processing, the cross-band texture procedure extracts more information than the single image texture analysis. Results show an improvement in average correct classification from 86.2% to 88.8% for ERTS image no. 1021-16333 with the cross-band texture procedure. However, when used together with spectral features, the single image texture plus spectral features perform better than the cross-band texture plus spectral features, with an average correct classification of 93.8% and 91.6%, respectively.
Universal Logarithmic Law of the Wall in Turbulent Channel and Pipe Flows
NASA Astrophysics Data System (ADS)
Zanoun, E.-S.; Durst, F.; Nagib, Hassan
2003-11-01
The accuracy of obtaining parameters of velocity distribution in the inertial sub-layer of wall-bounded flows depends on evaluating the wall friction and spatial resolution of measurements. By focusing on these aspects of experiments and extending the range of available channel data by a factor of two, our work confirms the log-law over a power-law representation for Re_τ≥ 2×10^3. Measurements in a fully-developed pipe reveal that velocity instruments such as hot-wires are superior to pressure probes for several reasons including spatial resolution. No general technique for correcting Pitot probe data exists, and the MacMillan's displacement correction drastically changes the slope of the logarithmic law. Oil-film interferometry coupled with hot-wire measurements were used to demonstrate effects of channel aspect ratio on results and to reveal that initial tripping has insignificant effects on the Kármán constant in the fully developed region. Data reveal evidence on differences in the outer flow between channels and pipes. In channels, we find that the inertial sub-range may be represented by the simple approximate formula ;U^+≈e ln y^++10/e and the fully developed channel resistance by c_f=0.0624 Re_m-0.25 or √2/c_f; ≈ ; e; ln Re √c_f+10/e+e;(ln1/√2-1).
Initial Validation of NDVI time seriesfrom AVHRR, VEGETATION, and MODIS
NASA Technical Reports Server (NTRS)
Morisette, Jeffrey T.; Pinzon, Jorge E.; Brown, Molly E.; Tucker, Jim; Justice, Christopher O.
2004-01-01
The paper will address Theme 7: Multi-sensor opportunities for VEGETATION. We present analysis of a long-term vegetation record derived from three moderate resolution sensors: AVHRR, VEGETATION, and MODIS. While empirically based manipulation can ensure agreement between the three data sets, there is a need to validate the series. This paper uses atmospherically corrected ETM+ data available over the EOS Land Validation Core Sites as an independent data set with which to compare the time series. We use ETM+ data from 15 globally distributed sites, 7 of which contain repeat coverage in time. These high-resolution data are compared to the values of each sensor by spatially aggregating the ETM+ to each specific sensors' spatial coverage. The aggregated ETM+ value provides a point estimate for a specific site on a specific date. The standard deviation of that point estimate is used to construct a confidence interval for that point estimate. The values from each moderate resolution sensor are then evaluated with respect to that confident interval. Result show that AVHRR, VEGETATION, and MODIS data can be combined to assess temporal uncertainties and address data continuity issues and that the atmospherically corrected ETM+ data provide an independent source with which to compare that record. The final product is a consistent time series climate record that links historical observations to current and future measurements.
Preliminary recognition of whole body vibration risk in private farmers' working environment.
Solecki, Leszek
2007-01-01
The objective of the study was the preliminary recognition of whole body mechanical vibration risk among farmers in the rural work environment. The study covered 15 farms using cultivated land of the size of over 10 ha, carrying out mixed production (plant-animal), equipped with agricultural tractors, and a basic set of tractor-mounted agricultural machinery, with a partial contribution of self-propelled agricultural machines. The scope of the study covered the measurements of effective vibration RMS acceleration (equivalent, maximum, minimum, peak) frequency corrected on the seats of agricultural vehicles in the three spatial directions of vibration (X, Y, Z). These measurements were realized while performing various field and transport work activities during the period of the whole year. A analysis of the peak, maximum and minimum vibration accelerations confirms that in the agricultural occupational environment there occurs a considerable variation of the vibration values registered. This is also evidenced by high values of the Crest Factor, sometimes exceeding a score of 10. Analysis of the registered equivalent values of vibration acceleration (frequency corrected) from the hygienic aspect showed that vibration occurring on the seats may create risk for farmers' health while performing such work activities as: tending and raking of hay, fertilizers spreading, soil aggregation, grass mowing and cultivation. Analysis of the spatial distribution of the measured, frequency corrected vibration accelerations indicates that considerably the highest acceleration values occur in the vertical plane (direction-Z). Literature data clearly confirm an unfavourable effect of whole body vibration present in agricultural vehicles on discomfort and the occurrence of back pain in the operators, especially in the low back region (lumbar spine), as well as degenerative changes in the spine.
NASA Astrophysics Data System (ADS)
Niederau, Jan; Ebigbo, Anozie; Freitag, Sebastian; Marquart, Gabriele; Clauser, Christoph
2014-05-01
Recent increase in exploration of the geothermal energy potential of the Perth Metropolitan Area (PMA) results in the need for reliable and robust reservoir models in order to explore rock properties and temperature distributions in the subsurface, where free convection in the main reservoir (Yarragadee Aquifer) is likely to occur [1]. While the structure of the Perth Basin has been refined recently, the heterogeneity and spatial complexity of permeability was up till now mainly neglected. An integrated, three dimensional tectonostratigraphic model of the PMA is constructed, using the modeling software '3D GeoModeller' and data of numerous artesian and petroleum wells. Comprising the region around the city of Perth, the model covers an area of about 5000 km2 up to a depth of 4.5 km, with focus on adequate representation of the main reservoir. We further construct a numerical model for fluid flow and heat transport in the Yarragadee Aquifer. Porosity distributions are deduced from well logs and linked to permeability by a calibrated correlation, based on a fractal approach. Three different cases are simulated using the FD code SHEMAT-Suite, in order to assess the influence of spatial heterogeneity of porosity and permeability on the development of free convection cells. constant porosity and permeability for the entire aquifer porosity and permeability decreasing with depth, thus reflecting compaction a conditional random permeability field within prescribed limits and for given correlation length In order to improve understanding of model correctness, as well as identification and comparison of convection cells in different simulations, we are developing a specialized visualization tool tailored to this purpose. The three different scenarios show distinctions in the distribution of convection cells. Where the Yarragadee Aquifer is in contact with overlying aquifers, regions of downflow develop. These in turn have a strong impact on the regional flow field and therefore temperature. The heterogeneous distribution of permeability seems to control the convection pattern on a smaller scale. References [1] Schilling, O., Sheldon, H.A., Reid, L.B., Corbel, S. 2013. Hydrothermal models of the Perth metropolitan area, Western Australia: implications for geothermal energy. Hydrogeology Journal, Vol. 21, 605-621.
An approach for drag correction based on the local heterogeneity for gas-solid flows
DOE Office of Scientific and Technical Information (OSTI.GOV)
Li, Tingwen; Wang, Limin; Rogers, William
2016-09-22
The drag models typically used for gas-solids interaction are mainly developed based on homogeneous systems of flow passing fixed particle assembly. It has been shown that the heterogeneous structures, i.e., clusters and bubbles in fluidized beds, need to be resolved to account for their effect in the numerical simulations. Since the heterogeneity is essentially captured through the local concentration gradient in the computational cells, this study proposes a simple approach to account for the non-uniformity of solids spatial distribution inside a computational cell and its effect on the interaction between gas and solid phases. Finally, to validate this approach, themore » predicted drag coefficient has been compared to the results from direct numerical simulations. In addition, the need to account for this type of heterogeneity is discussed for a periodic riser flow simulation with highly resolved numerical grids and the impact of the proposed correction for drag is demonstrated.« less
Comparison of vision through surface modulated and spatial light modulated multifocal optics.
Vinas, Maria; Dorronsoro, Carlos; Radhakrishnan, Aiswaryah; Benedi-Garcia, Clara; LaVilla, Edward Anthony; Schwiegerling, Jim; Marcos, Susana
2017-04-01
Spatial-light-modulators (SLM) are increasingly used as active elements in adaptive optics (AO) systems to simulate optical corrections, in particular multifocal presbyopic corrections. In this study, we compared vision with lathe-manufactured multi-zone (2-4) multifocal, angularly and radially, segmented surfaces and through the same corrections simulated with a SLM in a custom-developed two-active-element AO visual simulator. We found that perceived visual quality measured through real manufactured surfaces and SLM-simulated phase maps corresponded highly. Optical simulations predicted differences in perceived visual quality across different designs at Far distance, but showed some discrepancies at intermediate and near.
Comparison of vision through surface modulated and spatial light modulated multifocal optics
Vinas, Maria; Dorronsoro, Carlos; Radhakrishnan, Aiswaryah; Benedi-Garcia, Clara; LaVilla, Edward Anthony; Schwiegerling, Jim; Marcos, Susana
2017-01-01
Spatial-light-modulators (SLM) are increasingly used as active elements in adaptive optics (AO) systems to simulate optical corrections, in particular multifocal presbyopic corrections. In this study, we compared vision with lathe-manufactured multi-zone (2-4) multifocal, angularly and radially, segmented surfaces and through the same corrections simulated with a SLM in a custom-developed two-active-element AO visual simulator. We found that perceived visual quality measured through real manufactured surfaces and SLM-simulated phase maps corresponded highly. Optical simulations predicted differences in perceived visual quality across different designs at Far distance, but showed some discrepancies at intermediate and near. PMID:28736655
Thermal and Nonthermal Electron-ion Bremsstrahlung Spectrum from High-Temperature Plasmas
NASA Technical Reports Server (NTRS)
Jung, Young-Dae
1994-01-01
Electron-ion bremsstrahlung radiation from high-temperature plasmas is investigated. The first- and second-order Coulomb corrections in the nonrelativistic bremsstrahlung radiation power are obtained by the Elwert-Sommerfeld factor. In this paper, two cases of the electron distributions, the thermal and nonthermal power-law distributions, are considered. The inclusion of Coulomb corrections is necessary in deducing correctly the electron distribution function from radiation data. These results provide the correct information of electron distributions in high-temperature plasmas, such as in inertial confinement fusion plasmas and in the astrophysical hot thermal and nonthermal x-ray sources.
Jones, Mirkka M; Tuomisto, Hanna; Borcard, Daniel; Legendre, Pierre; Clark, David B; Olivas, Paulo C
2008-03-01
The degree to which variation in plant community composition (beta-diversity) is predictable from environmental variation, relative to other spatial processes, is of considerable current interest. We addressed this question in Costa Rican rain forest pteridophytes (1,045 plots, 127 species). We also tested the effect of data quality on the results, which has largely been overlooked in earlier studies. To do so, we compared two alternative spatial models [polynomial vs. principal coordinates of neighbour matrices (PCNM)] and ten alternative environmental models (all available environmental variables vs. four subsets, and including their polynomials vs. not). Of the environmental data types, soil chemistry contributed most to explaining pteridophyte community variation, followed in decreasing order of contribution by topography, soil type and forest structure. Environmentally explained variation increased moderately when polynomials of the environmental variables were included. Spatially explained variation increased substantially when the multi-scale PCNM spatial model was used instead of the traditional, broad-scale polynomial spatial model. The best model combination (PCNM spatial model and full environmental model including polynomials) explained 32% of pteridophyte community variation, after correcting for the number of sampling sites and explanatory variables. Overall evidence for environmental control of beta-diversity was strong, and the main floristic gradients detected were correlated with environmental variation at all scales encompassed by the study (c. 100-2,000 m). Depending on model choice, however, total explained variation differed more than fourfold, and the apparent relative importance of space and environment could be reversed. Therefore, we advocate a broader recognition of the impacts that data quality has on analysis results. A general understanding of the relative contributions of spatial and environmental processes to species distributions and beta-diversity requires that methodological artefacts are separated from real ecological differences.
Garcia-Vargas, Gonzalo G; Rothenberg, Stephen J; Silbergeld, Ellen K; Weaver, Virginia; Zamoiski, Rachel; Resnick, Carol; Rubio-Andrade, Marisela; Parsons, Patrick J; Steuerwald, Amy J; Navas-Acién, Ana; Guallar, Eliseo
2014-11-01
High blood lead (BPb) levels in children and elevated soil and dust arsenic, cadmium, and lead were previously found in Torreón, northern Mexico, host to the world's fourth largest lead-zinc metal smelter. The objectives of this study were to determine spatial distributions of adolescents with higher BPb and creatinine-corrected urine total arsenic, cadmium, molybdenum, thallium, and uranium around the smelter. Cross-sectional study of 512 male and female subjects 12-15 years of age was conducted. We measured BPb by graphite furnace atomic absorption spectrometry and urine trace elements by inductively coupled plasma-mass spectrometry, with dynamic reaction cell mode for arsenic. We constructed multiple regression models including sociodemographic variables and adjusted for subject residence spatial correlation with spatial lag or error terms. We applied local indicators of spatial association statistics to model residuals to identify hot spots of significant spatial clusters of subjects with higher trace elements. We found spatial clusters of subjects with elevated BPb (range 3.6-14.7 μg/dl) and urine cadmium (0.18-1.14 μg/g creatinine) adjacent to and downwind of the smelter and elevated urine thallium (0.28-0.93 μg/g creatinine) and uranium (0.07-0.13 μg/g creatinine) near ore transport routes, former waste, and industrial discharge sites. The conclusion derived from this study was that spatial clustering of adolescents with high BPb and urine cadmium adjacent to and downwind of the smelter and residual waste pile, areas identified over a decade ago with high lead and cadmium in soil and dust, suggests that past and/or present plant operations continue to present health risks to children in those neighborhoods.
Garcia-Vargas, Gonzalo G.; Rothenberg, Stephen J.; Silbergeld, Ellen K.; Weaver, Virginia; Zamoiski, Rachel; Resnick, Carol; Rubio-Andrade, Marisela; Parsons, Patrick J.; Steuerwald, Amy J.; Navas-Acién, Ana; Guallar, Eliseo
2016-01-01
High blood lead (BPb) levels in children and elevated soil and dust arsenic, cadmium, and lead were previously found in Torreón, northern Mexico, host to the world’s fourth largest lead–zinc metal smelter. The objectives of this study were to determine spatial distributions of adolescents with higher BPb and creatinine-corrected urine total arsenic, cadmium, molybdenum, thallium, and uranium around the smelter. Cross-sectional study of 512 male and female subjects 12–15 years of age was conducted. We measured BPb by graphite furnace atomic absorption spectrometry and urine trace elements by inductively coupled plasma-mass spectrometry, with dynamic reaction cell mode for arsenic. We constructed multiple regression models including sociodemographic variables and adjusted for subject residence spatial correlation with spatial lag or error terms. We applied local indicators of spatial association statistics to model residuals to identify hot spots of significant spatial clusters of subjects with higher trace elements. We found spatial clusters of subjects with elevated BPb (range 3.6–14.7 µg/dl) and urine cadmium (0.18–1.14 µg/g creatinine) adjacent to and downwind of the smelter and elevated urine thallium (0.28–0.93 µg/g creatinine) and uranium (0.07–0.13 µg/g creatinine) near ore transport routes, former waste, and industrial discharge sites. The conclusion derived from this study was that spatial clustering of adolescents with high BPb and urine cadmium adjacent to and downwind of the smelter and residual waste pile, areas identified over a decade ago with high lead and cadmium in soil and dust, suggests that past and/or present plant operations continue to present health risks to children in those neighborhoods. PMID:24549228
Photometric Modeling and VIS-IR Albedo Maps of Dione From Cassini-VIMS
NASA Astrophysics Data System (ADS)
Filacchione, G.; Ciarniello, M.; D'Aversa, E.; Capaccioni, F.; Cerroni, P.; Buratti, B. J.; Clark, R. N.; Stephan, K.; Plainaki, C.
2018-03-01
We report about visible and infrared albedo maps and spectral indicators of Dione's surface derived from the complete Visual and Infrared Mapping Spectrometer (VIMS) data set acquired between 2004 and 2017 during the Cassini tour in Saturn's system. Maps are derived by applying a photometric correction necessary to disentangle the intrinsic albedo of the surface from illumination and viewing geometry occurring at the time of the observation. The photometric correction is based on the Shkuratov et al. (2011, https://doi.org/10.1016/j.pss.2011.06.011) method which yields values of the surface equigonal albedo. Dione's surface albedo maps are rendered at five visible (VIS: 0.35, 0.44, 0.55, 0.7, and 0.95 μm) and five infrared (IR: 1.046, 1.540, 1.822, 2.050, and 2.200 μm) wavelengths in cylindrical projection with a 0.5° × 0.5° angular resolution in latitude and longitude, corresponding to a spatial resolution of 4.5 km/bin. Apart from visible and infrared albedo maps, we report about the distribution of the two visible spectral slopes (0.35-0.55 and 0.55-0.95 μm) and water ice 2.050 μm band depth computed after having applied the photometric correction. The derived spectral indicators are employed to trace Dione's composition variability on both global and local scales allowing to study the dichotomy between the bright-leading and dark-trailing hemispheres, the distribution of fresh material on the impact craters and surrounding ejecta, and the resurfacing of the bright material within the chasmata caused by tectonism.
NASA Astrophysics Data System (ADS)
Lee, J.
2013-12-01
Ground-Based Augmentation Systems (GBAS) support aircraft precision approach and landing by providing differential GPS corrections to aviation users. For GBAS applications, most of ionospheric errors are removed by applying the differential corrections. However, ionospheric correction errors may exist due to ionosphere spatial decorrelation between GBAS ground facility and users. Thus, the standard deviation of ionosphere spatial decorrelation (σvig) is estimated and included in the computation of error bounds on user position solution. The σvig of 4mm/km, derived for the Conterminous United States (CONUS), bounds one-sigma ionospheric spatial gradients under nominal conditions (including active, but not stormy condition) with an adequate safety margin [1]. The conservatism residing in the current σvig by fixing it to a constant value for all non-stormy conditions could be mitigated by subdividing ionospheric conditions into several classes and using different σvig for each class. This new concept, real-time σvig adaptation, will be possible if the level of ionospheric activity can be well classified based on space weather intensity. This paper studies correlation between the statistics of nominal ionospheric spatial gradients and space weather indices. The analysis was carried out using two sets of data collected from Continuous Operating Reference Station (CORS) Network; 9 consecutive (nominal and ionospherically active) days in 2004 and 19 consecutive (relatively 'quiet') days in 2010. Precise ionospheric delay estimates are obtained using the simplified truth processing method and vertical ionospheric gradients are computed using the well-known 'station pair method' [2]. The remaining biases which include carrier-phase leveling errors and Inter-frequency Bias (IFB) calibration errors are reduced by applying linear slip detection thresholds. The σvig was inflated to overbound the distribution of vertical ionospheric gradients with the required confidence level. Using the daily maximum values of σvig, day-to-day variations of spatial gradients are compared to those of two space weather indices; Disturbance, Storm Time (Dst) index and Interplanetary Magnetic Field Bz (IMF Bz). The day-to-day variations of both space weather indices showed a good agreement with those of daily maximum σvig. The results demonstrate that ionospheric gradient statistics are highly correlated with space weather indices on nominal and off-nominal days. Further investigation on this relationship would facilitate prediction of upcoming ionospheric behavior based on space weather information and adjusting σvig in real time. Consequently it will improve GBAS availability by adding external information to operation. [1] Lee, J., S. Pullen, S. Datta-Barua, and P. Enge (2007), Assessment of ionosphere spatial decorrelation for GPS-based aircraft landing systems, J. Aircraft, 44(5), 1662-1669, doi:10.2514/1.28199. [2] Jung, S., and J. Lee (2012), Long-term ionospheric anomaly monitoring for ground based augmentation systems, Radio Sci., 47, RS4006, doi:10.1029/2012RS005016.
Chebli, Youssef; Kaneda, Minako; Zerzour, Rabah; Geitmann, Anja
2012-12-01
The pollen tube is a cellular protuberance formed by the pollen grain, or male gametophyte, in flowering plants. Its principal metabolic activity is the synthesis and assembly of cell wall material, which must be precisely coordinated to sustain the characteristic rapid growth rate and to ensure geometrically correct and efficient cellular morphogenesis. Unlike other model species, the cell wall of the Arabidopsis (Arabidopsis thaliana) pollen tube has not been described in detail. We used immunohistochemistry and quantitative image analysis to provide a detailed profile of the spatial distribution of the major cell wall polymers composing the Arabidopsis pollen tube cell wall. Comparison with predictions made by a mechanical model for pollen tube growth revealed the importance of pectin deesterification in determining the cell diameter. Scanning electron microscopy demonstrated that cellulose microfibrils are oriented in near longitudinal orientation in the Arabidopsis pollen tube cell wall, consistent with a linear arrangement of cellulose synthase CESA6 in the plasma membrane. The cellulose label was also found inside cytoplasmic vesicles and might originate from an early activation of cellulose synthases prior to their insertion into the plasma membrane or from recycling of short cellulose polymers by endocytosis. A series of strategic enzymatic treatments also suggests that pectins, cellulose, and callose are highly cross linked to each other.
Microcystic macular edema detection in retina OCT images
NASA Astrophysics Data System (ADS)
Swingle, Emily K.; Lang, Andrew; Carass, Aaron; Ying, Howard S.; Calabresi, Peter A.; Prince, Jerry L.
2014-03-01
Optical coherence tomography (OCT) is a powerful imaging tool that is particularly useful for exploring retinal abnormalities in ophthalmological diseases. Recently, it has been used to track changes in the eye associated with neurological diseases such as multiple sclerosis (MS) where certain tissue layer thicknesses have been associated with disease progression. A small percentage of MS patients also exhibit what has been called microcystic macular edema (MME), where uid collections that are thought to be pseudocysts appear in the inner nuclear layer. Very little is known about the cause of this condition so it is important to be able to identify precisely where these pseudocysts occur within the retina. This identi cation would be an important rst step towards furthering our understanding. In this work, we present a detection algorithm to nd these pseudocysts and to report on their spatial distribution. Our approach uses a random forest classi er trained on manual segmentation data to classify each voxel as pseudocyst or not. Despite having a small sample size of ve subjects, the algorithm correctly identi es 84.6% of pseudocysts as compared to manual delineation. Finally, using our method, we show that the spatial distribution of pseudocysts within the macula are generally contained within an annulus around the fovea.
Spatial analysis of cities using Renyi entropy and fractal parameters
NASA Astrophysics Data System (ADS)
Chen, Yanguang; Feng, Jian
2017-12-01
The spatial distributions of cities fall into two groups: one is the simple distribution with characteristic scale (e.g. exponential distribution), and the other is the complex distribution without characteristic scale (e.g. power-law distribution). The latter belongs to scale-free distributions, which can be modeled with fractal geometry. However, fractal dimension is not suitable for the former distribution. In contrast, spatial entropy can be used to measure any types of urban distributions. This paper is devoted to generalizing multifractal parameters by means of dual relation between Euclidean and fractal geometries. The main method is mathematical derivation and empirical analysis, and the theoretical foundation is the discovery that the normalized fractal dimension is equal to the normalized entropy. Based on this finding, a set of useful spatial indexes termed dummy multifractal parameters are defined for geographical analysis. These indexes can be employed to describe both the simple distributions and complex distributions. The dummy multifractal indexes are applied to the population density distribution of Hangzhou city, China. The calculation results reveal the feature of spatio-temporal evolution of Hangzhou's urban morphology. This study indicates that fractal dimension and spatial entropy can be combined to produce a new methodology for spatial analysis of city development.
Duerden, E G; Foong, J; Chau, V; Branson, H; Poskitt, K J; Grunau, R E; Synnes, A; Zwicker, J G; Miller, S P
2015-08-01
Adverse neurodevelopmental outcome is common in children born preterm. Early sensitive predictors of neurodevelopmental outcome such as MR imaging are needed. Tract-based spatial statistics, a diffusion MR imaging analysis method, performed at term-equivalent age (40 weeks) is a promising predictor of neurodevelopmental outcomes in children born very preterm. We sought to determine the association of tract-based spatial statistics findings before term-equivalent age with neurodevelopmental outcome at 18-months corrected age. Of 180 neonates (born at 24-32-weeks' gestation) enrolled, 153 had DTI acquired early at 32 weeks' postmenstrual age and 105 had DTI acquired later at 39.6 weeks' postmenstrual age. Voxelwise statistics were calculated by performing tract-based spatial statistics on DTI that was aligned to age-appropriate templates. At 18-month corrected age, 166 neonates underwent neurodevelopmental assessment by using the Bayley Scales of Infant Development, 3rd ed, and the Peabody Developmental Motor Scales, 2nd ed. Tract-based spatial statistics analysis applied to early-acquired scans (postmenstrual age of 30-33 weeks) indicated a limited significant positive association between motor skills and axial diffusivity and radial diffusivity values in the corpus callosum, internal and external/extreme capsules, and midbrain (P < .05, corrected). In contrast, for term scans (postmenstrual age of 37-41 weeks), tract-based spatial statistics analysis showed a significant relationship between both motor and cognitive scores with fractional anisotropy in the corpus callosum and corticospinal tracts (P < .05, corrected). Tract-based spatial statistics in a limited subset of neonates (n = 22) scanned at <30 weeks did not significantly predict neurodevelopmental outcomes. The strength of the association between fractional anisotropy values and neurodevelopmental outcome scores increased from early-to-late-acquired scans in preterm-born neonates, consistent with brain dysmaturation in this population. © 2015 by American Journal of Neuroradiology.
NASA Astrophysics Data System (ADS)
Lapshin, Rostislav V.
2016-08-01
A method of distributed calibration of a probe microscope scanner is suggested. The main idea consists in a search for a net of local calibration coefficients (LCCs) in the process of automatic measurement of a standard surface, whereby each point of the movement space of the scanner can be characterized by a unique set of scale factors. Feature-oriented scanning (FOS) methodology is used as a basis for implementation of the distributed calibration permitting to exclude in situ the negative influence of thermal drift, creep and hysteresis on the obtained results. Possessing the calibration database enables correcting in one procedure all the spatial systematic distortions caused by nonlinearity, nonorthogonality and spurious crosstalk couplings of the microscope scanner piezomanipulators. To provide high precision of spatial measurements in nanometer range, the calibration is carried out using natural standards - constants of crystal lattice. One of the useful modes of the developed calibration method is a virtual mode. In the virtual mode, instead of measurement of a real surface of the standard, the calibration program makes a surface image ;measurement; of the standard, which was obtained earlier using conventional raster scanning. The application of the virtual mode permits simulation of the calibration process and detail analysis of raster distortions occurring in both conventional and counter surface scanning. Moreover, the mode allows to estimate the thermal drift and the creep velocities acting while surface scanning. Virtual calibration makes possible automatic characterization of a surface by the method of scanning probe microscopy (SPM).
The Potential for Spatial Distribution Indices to Signal Thresholds in Marine Fish Biomass
Reuchlin-Hugenholtz, Emilie
2015-01-01
The frequently observed positive relationship between fish population abundance and spatial distribution suggests that changes in distribution can be indicative of trends in abundance. If contractions in spatial distribution precede declines in spawning stock biomass (SSB), spatial distribution reference points could complement the SSB reference points that are commonly used in marine conservation biology and fisheries management. When relevant spatial distribution information is integrated into fisheries management and recovery plans, risks and uncertainties associated with a plan based solely on the SSB criterion would be reduced. To assess the added value of spatial distribution data, we examine the relationship between SSB and four metrics of spatial distribution intended to reflect changes in population range, concentration, and density for 10 demersal populations (9 species) inhabiting the Scotian Shelf, Northwest Atlantic. Our primary purpose is to assess their potential to serve as indices of SSB, using fisheries independent survey data. We find that metrics of density offer the best correlate of spawner biomass. A decline in the frequency of encountering high density areas is associated with, and in a few cases preceded by, rapid declines in SSB in 6 of 10 populations. Density-based indices have considerable potential to serve both as an indicator of SSB and as spatially based reference points in fisheries management. PMID:25789624
Tensor perturbations during inflation in a spatially closed Universe
DOE Office of Scientific and Technical Information (OSTI.GOV)
Bonga, Béatrice; Gupt, Brajesh; Yokomizo, Nelson, E-mail: bpb165@psu.edu, E-mail: bgupt@gravity.psu.edu, E-mail: yokomizo@gravity.psu.edu
2017-05-01
In a recent paper [1], we studied the evolution of the background geometry and scalar perturbations in an inflationary, spatially closed Friedmann-Lemaȋtre-Robertson-Walker (FLRW) model having constant positive spatial curvature and spatial topology S{sup 3}. Due to the spatial curvature, the early phase of slow-roll inflation is modified, leading to suppression of power in the scalar power spectrum at large angular scales. In this paper, we extend the analysis to include tensor perturbations. We find that, similarly to the scalar perturbations, the tensor power spectrum also shows suppression for long wavelength modes. The correction to the tensor spectrum is limited tomore » the very long wavelength modes, therefore the resulting observable CMB B-mode polarization spectrum remains practically the same as in the standard scenario with flat spatial sections. However, since both the tensor and scalar power spectra are modified, there are scale dependent corrections to the tensor-to-scalar ratio that leads to violation of the standard slow-roll consistency relation.« less
Design and implementation of a distributed large-scale spatial database system based on J2EE
NASA Astrophysics Data System (ADS)
Gong, Jianya; Chen, Nengcheng; Zhu, Xinyan; Zhang, Xia
2003-03-01
With the increasing maturity of distributed object technology, CORBA, .NET and EJB are universally used in traditional IT field. However, theories and practices of distributed spatial database need farther improvement in virtue of contradictions between large scale spatial data and limited network bandwidth or between transitory session and long transaction processing. Differences and trends among of CORBA, .NET and EJB are discussed in details, afterwards the concept, architecture and characteristic of distributed large-scale seamless spatial database system based on J2EE is provided, which contains GIS client application, web server, GIS application server and spatial data server. Moreover the design and implementation of components of GIS client application based on JavaBeans, the GIS engine based on servlet, the GIS Application server based on GIS enterprise JavaBeans(contains session bean and entity bean) are explained.Besides, the experiments of relation of spatial data and response time under different conditions are conducted, which proves that distributed spatial database system based on J2EE can be used to manage, distribute and share large scale spatial data on Internet. Lastly, a distributed large-scale seamless image database based on Internet is presented.
Decapod larvae distribution and species composition off the southern Portuguese coast
NASA Astrophysics Data System (ADS)
Pochelon, Patricia N.; Pires, Rita F. T.; Dubert, Jesús; Nolasco, Rita; Santos, A. Miguel P.; Queiroga, Henrique; dos Santos, Antonina
2017-12-01
For decapod crustaceans, the larval phase is the main responsible for dispersal, given the direct emission from adult habitats into the water column. Circulation patterns and behavioural mechanisms control the dispersal distance and connectivity between different areas. Information on larval distribution and abundance is required to predict the size and location of breeding populations, and correctly manage marine resources. Spatial distribution and abundance data of decapod larvae, and environmental parameters were assessed in winter surveys off the southern Portuguese coast. To better understand the oceanic structures driving larval distribution patterns, in situ physical parameters were measured and a hydrodynamical model used. Inter-annual, cross-shore and alongshore differences on decapod larvae distribution were found. Brachyuran crabs dominated the samples and similar taxa composition was observed in the most dynamic areas. Coastal taxa dominated the nearshore survey and were almost absent in the more offshore one, that registered much lower abundances. An upwelling front allowed a clear cross-shore species separation, also evident in the abundance values and number of taxa. Hydrodynamical conditions and adult habitats were the main factors explaining the observed patterns. Important missing information to understand the distribution patterns of decapod larval communities and the mechanisms behind them is given for the region.
Drisdelle, Brandi Lee; Aubin, Sébrina; Jolicoeur, Pierre
2017-01-01
The objective of the present study was to assess the robustness and reliability of independent component analysis (ICA) as a method for ocular artifact correction in electrophysiological studies of visual-spatial attention and memory. The N2pc and sustained posterior contralateral negativity (SPCN), electrophysiological markers of visual-spatial attention and memory, respectively, are lateralized posterior ERPs typically observed following the presentation of lateral stimuli (targets and distractors) along with instructions to maintain fixation on the center of the visual search for the entire trial. Traditionally, trials in which subjects may have displaced their gaze are rejected based on a cutoff threshold, minimizing electrophysiological contamination by saccades. Given the loss of data resulting from rejection, we examined ocular correction by comparing results using standard fixation instructions against a condition where subjects were instructed to shift their gaze toward possible targets. Both conditions were analyzed using a rejection threshold and ICA correction for saccade activity management. Results demonstrate that ICA conserves data that would have otherwise been removed and leaves the underlying neural activity intact, as demonstrated by experimental manipulations previously shown to modulate the N2pc and the SPCN. Not only does ICA salvage and not distort data, but also large eye movements had only subtle effects. Overall, the findings provide convincing evidence for ICA correction for not only special cases (e.g., subjects did not follow fixation instruction) but also as a candidate for standard ocular artifact management in electrophysiological studies interested in visual-spatial attention and memory. © 2016 Society for Psychophysiological Research.
Dan, Haruka; Azuma, Teruaki; Hayakawa, Fumiyo; Kohyama, Kaoru
2005-05-01
This study was designed to examine human subjects' ability to discriminate between spatially different bite pressures. We measured actual bite pressure distribution when subjects simultaneously bit two silicone rubber samples with different hardnesses using their right and left incisors. They were instructed to compare the hardness of these two rubber samples and indicate which was harder (right or left). The correct-answer rates were statistically significant at P < 0.05 for all pairs of different right and left silicone rubber hardnesses. Simultaneous bite measurements using a multiple-point sheet sensor demonstrated that the bite force, active pressure and maximum pressure point were greater for the harder silicone rubber sample. The difference between the left and right was statistically significant (P < 0.05) for all pairs with different silicone rubber hardnesses. We demonstrated for the first time that subjects could perceive and discriminate between spatially different bite pressures during a single bite with incisors. Differences of the bite force, pressure and the maximum pressure point between the right and left silicone samples should be sensory cues for spatial hardness discrimination.
NASA Astrophysics Data System (ADS)
van der Veen, Rob L. P.; Berendschot, Tos T. J. M.; Makridaki, Maria; Hendrikse, Fred; Carden, David; Murray, Ian J.
2009-11-01
A comparison of macular pigment optical density (MPOD) spatial profiles determined by an optical and a psychophysical technique is presented. We measured the right eyes of 19 healthy individuals, using fundus reflectometry at 0, 1, 2, 4, 6, and 8 deg eccentricity; and heterochromatic flicker photometry (HFP) at 0, 0.5, 1, 2, 3, 4, 5, 6, and 7 deg, and a reference point at 8 deg eccentricity. We found a strong correlation between the two techniques. However, the absolute estimates obtained by fundus reflectometry data were higher than by HFP. These differences could partly be explained by the fact that at 8 deg eccentricity the MPOD is not zero, as assumed in HFP. Furthermore, when performing HFP for eccentricities of <1 deg, we had to assume that subjects set flicker thresholds at 0.4 deg horizontal translation when using a 1-deg stimulus. MPOD profiles are very similar for both techniques if, on average, 0.05 DU is added to the HFP data at all eccentricities. An additional correction factor, dependent on the steepness of the MPOD spatial distribution, is required for 0 deg.
Quantum error-correction failure distributions: Comparison of coherent and stochastic error models
NASA Astrophysics Data System (ADS)
Barnes, Jeff P.; Trout, Colin J.; Lucarelli, Dennis; Clader, B. D.
2017-06-01
We compare failure distributions of quantum error correction circuits for stochastic errors and coherent errors. We utilize a fully coherent simulation of a fault-tolerant quantum error correcting circuit for a d =3 Steane and surface code. We find that the output distributions are markedly different for the two error models, showing that no simple mapping between the two error models exists. Coherent errors create very broad and heavy-tailed failure distributions. This suggests that they are susceptible to outlier events and that mean statistics, such as pseudothreshold estimates, may not provide the key figure of merit. This provides further statistical insight into why coherent errors can be so harmful for quantum error correction. These output probability distributions may also provide a useful metric that can be utilized when optimizing quantum error correcting codes and decoding procedures for purely coherent errors.
A New Method for Atmospheric Correction of MRO/CRISM Data.
NASA Astrophysics Data System (ADS)
Noe Dobrea, Eldar Z.; Dressing, C.; Wolff, M. J.
2009-09-01
The Compact Reconnaissance Imaging Spectrometer for Mars (CRISM) aboard the Mars Reconnaissance Orbiter (MRO) collects hyperspectral images from 0.362 to 3.92 μm at 6.55 nanometers/channel, and at a spatial resolution of 20 m/pixel. The 1-2.6 μm spectral range is often used to identify and map the distribution of hydrous minerals using mineralogically diagnostic bands at 1.4 μm, 1.9 μm, and 2 - 2.5 micron region. Atmospheric correction of the 2-μm CO2 band typically employs the same methodology applied to OMEGA data (Mustard et al., Nature 454, 2008): an atmospheric opacity spectrum, obtained from the ratio of spectra from the base to spectra from the peak of Olympus Mons, is rescaled for each spectrum in the observation to fit the 2-μm CO2 band, and is subsequently used to correct the data. Three important aspects are not considered in this correction: 1) absorptions due to water vapor are improperly accounted for, 2) the band-center of each channel shifts slightly with time, and 3) multiple scattering due to atmospheric aerosols is not considered. The second issue results in miss-registration of the sharp CO2 features in the 2-μm triplet, and hence poor atmospheric correction. This leads to the necessity to ratio all spectra using the spectrum of a spectrally "bland” region in each observation in order to distinguish features 1.9 μm. Here, we present an improved atmospheric correction method, which uses emission phase function (EPF) observations to correct for molecular opacity, and a discrete ordinate radiative transfer algorithm (DISORT - Stamnes et al., Appl. Opt. 27, 1988) to correct for the effects of multiple scattering. This method results in a significant improvement in the correction of the 2-μm CO2 band, allowing us to forgo the use of spectral ratios that affect the spectral shape and preclude the derivation of reflectance values in the data.
A class of renormalised meshless Laplacians for boundary value problems
NASA Astrophysics Data System (ADS)
Basic, Josip; Degiuli, Nastia; Ban, Dario
2018-02-01
A meshless approach to approximating spatial derivatives on scattered point arrangements is presented in this paper. Three various derivations of approximate discrete Laplace operator formulations are produced using the Taylor series expansion and renormalised least-squares correction of the first spatial derivatives. Numerical analyses are performed for the introduced Laplacian formulations, and their convergence rate and computational efficiency are examined. The tests are conducted on regular and highly irregular scattered point arrangements. The results are compared to those obtained by the smoothed particle hydrodynamics method and the finite differences method on a regular grid. Finally, the strong form of various Poisson and diffusion equations with Dirichlet or Robin boundary conditions are solved in two and three dimensions by making use of the introduced operators in order to examine their stability and accuracy for boundary value problems. The introduced Laplacian operators perform well for highly irregular point distribution and offer adequate accuracy for mesh and mesh-free numerical methods that require frequent movement of the grid or point cloud.
NASA Astrophysics Data System (ADS)
Chérigier, L.; Czarnetzki, U.; Luggenhölscher, D.; Schulz-von der Gathen, V.; Döbele, H. F.
1999-01-01
Absolute atomic hydrogen densities were measured in the gaseous electronics conference reference cell parallel plate reactor by Doppler-free two-photon absorption laser induced fluorescence spectroscopy (TALIF) at λ=205 nm. The capacitively coupled radio frequency discharge was operated at 13.56 MHz in pure hydrogen under various input power and pressure conditions. The Doppler-free excitation technique with an unfocused laser beam together with imaging the fluorescence radiation by an intensified charge coupled device camera allows instantaneous spatial resolution along the radial direction. Absolute density calibration is obtained with the aid of a flow tube reactor and titration with NO2. The influence of spatial intensity inhomogenities along the laser beam and subsequent fluorescence are corrected by TALIF in xenon. A full mapping of the absolute density distribution between the electrodes was obtained. The detection limit for atomic hydrogen amounts to about 2×1018 m-3. The dissociation degree is of the order of a few percent.
NASA Astrophysics Data System (ADS)
Yu, X.; Salama, S.; Shen, F.
2016-08-01
During the Dragon-3 project (ID: 10555) period, we developed and improved the atmospheric correction algorithms (AC) and retrieval models of suspended sediment concentration ( ) and diffuse attenuation coefficient ( ) for the Yangtze estuarine and coastal waters. The developed models were validated by measurements with consistently stable and fairly accurate estimations, reproducing reasonable distribution maps of and over the study area. Spatial-temporal variations of were presented and the mechanisms of the sediment transport were discussed. We further examined the compatibility of the developed AC algorithms and retrieval model and the consistency of satellite products for multi-sensor such as MODIS/Terra/Aqua, MERIS/Envisat, MERSI/ FY-3 and GOCI. The inter-comparison of multi- sensor suggested that different satellite products can be combined to increase revisit frequency and complement a temporal gap of time series satellites that may exist between on-orbit and off- orbit, facilitating a better monitor on the spatial- temporal dynamics of .
Phase derivative method for reconstruction of slightly off-axis digital holograms.
Guo, Cheng-Shan; Wang, Ben-Yi; Sha, Bei; Lu, Yu-Jie; Xu, Ming-Yuan
2014-12-15
A phase derivative (PD) method is proposed for reconstruction of off-axis holograms. In this method, a phase distribution of the tested object wave constrained within 0 to pi radian is firstly worked out by a simple analytical formula; then it is corrected to its right range from -pi to pi according to the sign characteristics of its first-order derivative. A theoretical analysis indicates that this PD method is particularly suitable for reconstruction of slightly off-axis holograms because it only requires the spatial frequency of the reference beam larger than spatial frequency of the tested object wave in principle. In addition, because the PD method belongs to a pure local method with no need of any integral operation or phase shifting algorithm in process of the phase retrieval, it could have some advantages in reducing computer load and memory requirements to the image processing system. Some experimental results are given to demonstrate the feasibility of the method.
The effect of retrosplenial cortex lesions in rats on incidental and active spatial learning
Nelson, A. J. D.; Hindley, E. L.; Pearce, J. M.; Vann, S. D.; Aggleton, J. P.
2015-01-01
The study examined the importance of the retrosplenial cortex for the incidental learning of the spatial arrangement of distinctive features within a scene. In a modified Morris water-maze, rats spontaneously learnt the location of an escape platform prior to swimming to that location. For this, rats were repeatedly placed on a submerged platform in one corner of either a rectangular (Experiment 1) or square (Experiments 2, 3) pool with walls of different appearance. The rats were then released in the center of the pool for their first test trial. In Experiment 1, the correct corner and its diagonally opposite partner (also correct) were specified by the geometric properties of the pool. Rats with retrosplenial lesions took longer to first reach a correct corner, subsequently showing an attenuated preference for the correct corners. A reduced preference for the correct corner was also found in Experiment 2, when platform location was determined by the juxtaposition of highly salient visual cues (black vs. white walls). In Experiment 3, less salient visual cues (striped vs. white walls) led to a robust lesion impairment, as the retrosplenial lesioned rats showed no preference for the correct corner. When subsequently trained actively to swim to the correct corner over successive trials, retrosplenial lesions spared performance on all three discriminations. The findings not only reveal the importance of the retrosplenial cortex for processing various classes of visuospatial information but also highlight a broader role in the incidental learning of the features of a spatial array, consistent with the translation of scene information. PMID:25705182
Analysis of skin tissues spatial fluorescence distribution by the Monte Carlo simulation
NASA Astrophysics Data System (ADS)
Y Churmakov, D.; Meglinski, I. V.; Piletsky, S. A.; Greenhalgh, D. A.
2003-07-01
A novel Monte Carlo technique of simulation of spatial fluorescence distribution within the human skin is presented. The computational model of skin takes into account the spatial distribution of fluorophores, which would arise due to the structure of collagen fibres, compared to the epidermis and stratum corneum where the distribution of fluorophores is assumed to be homogeneous. The results of simulation suggest that distribution of auto-fluorescence is significantly suppressed in the near-infrared spectral region, whereas the spatial distribution of fluorescence sources within a sensor layer embedded in the epidermis is localized at an `effective' depth.
Correction of Spatial Bias in Oligonucleotide Array Data
Lemieux, Sébastien
2013-01-01
Background. Oligonucleotide microarrays allow for high-throughput gene expression profiling assays. The technology relies on the fundamental assumption that observed hybridization signal intensities (HSIs) for each intended target, on average, correlate with their target's true concentration in the sample. However, systematic, nonbiological variation from several sources undermines this hypothesis. Background hybridization signal has been previously identified as one such important source, one manifestation of which appears in the form of spatial autocorrelation. Results. We propose an algorithm, pyn, for the elimination of spatial autocorrelation in HSIs, exploiting the duality of desirable mutual information shared by probes in a common probe set and undesirable mutual information shared by spatially proximate probes. We show that this correction procedure reduces spatial autocorrelation in HSIs; increases HSI reproducibility across replicate arrays; increases differentially expressed gene detection power; and performs better than previously published methods. Conclusions. The proposed algorithm increases both precision and accuracy, while requiring virtually no changes to users' current analysis pipelines: the correction consists merely of a transformation of raw HSIs (e.g., CEL files for Affymetrix arrays). A free, open-source implementation is provided as an R package, compatible with standard Bioconductor tools. The approach may also be tailored to other platform types and other sources of bias. PMID:23573083
NASA Astrophysics Data System (ADS)
Demirel, M. C.; Mai, J.; Stisen, S.; Mendiguren González, G.; Koch, J.; Samaniego, L. E.
2016-12-01
Distributed hydrologic models are traditionally calibrated and evaluated against observations of streamflow. Spatially distributed remote sensing observations offer a great opportunity to enhance spatial model calibration schemes. For that it is important to identify the model parameters that can change spatial patterns before the satellite based hydrologic model calibration. Our study is based on two main pillars: first we use spatial sensitivity analysis to identify the key parameters controlling the spatial distribution of actual evapotranspiration (AET). Second, we investigate the potential benefits of incorporating spatial patterns from MODIS data to calibrate the mesoscale Hydrologic Model (mHM). This distributed model is selected as it allows for a change in the spatial distribution of key soil parameters through the calibration of pedo-transfer function parameters and includes options for using fully distributed daily Leaf Area Index (LAI) directly as input. In addition the simulated AET can be estimated at the spatial resolution suitable for comparison to the spatial patterns observed using MODIS data. We introduce a new dynamic scaling function employing remotely sensed vegetation to downscale coarse reference evapotranspiration. In total, 17 parameters of 47 mHM parameters are identified using both sequential screening and Latin hypercube one-at-a-time sampling methods. The spatial patterns are found to be sensitive to the vegetation parameters whereas streamflow dynamics are sensitive to the PTF parameters. The results of multi-objective model calibration show that calibration of mHM against observed streamflow does not reduce the spatial errors in AET while they improve only the streamflow simulations. We will further examine the results of model calibration using only multi spatial objective functions measuring the association between observed AET and simulated AET maps and another case including spatial and streamflow metrics together.
Two-compartment modeling of tissue microcirculation revisited.
Brix, Gunnar; Salehi Ravesh, Mona; Griebel, Jürgen
2017-05-01
Conventional two-compartment modeling of tissue microcirculation is used for tracer kinetic analysis of dynamic contrast-enhanced (DCE) computed tomography or magnetic resonance imaging studies although it is well-known that the underlying assumption of an instantaneous mixing of the administered contrast agent (CA) in capillaries is far from being realistic. It was thus the aim of the present study to provide theoretical and computational evidence in favor of a conceptually alternative modeling approach that makes it possible to characterize the bias inherent to compartment modeling and, moreover, to approximately correct for it. Starting from a two-region distributed-parameter model that accounts for spatial gradients in CA concentrations within blood-tissue exchange units, a modified lumped two-compartment exchange model was derived. It has the same analytical structure as the conventional two-compartment model, but indicates that the apparent blood flow identifiable from measured DCE data is substantially overestimated, whereas the three other model parameters (i.e., the permeability-surface area product as well as the volume fractions of the plasma and interstitial distribution space) are unbiased. Furthermore, a simple formula was derived to approximately compute a bias-corrected flow from the estimates of the apparent flow and permeability-surface area product obtained by model fitting. To evaluate the accuracy of the proposed modeling and bias correction method, representative noise-free DCE curves were analyzed. They were simulated for 36 microcirculation and four input scenarios by an axially distributed reference model. As analytically proven, the considered two-compartment exchange model is structurally identifiable from tissue residue data. The apparent flow values estimated for the 144 simulated tissue/input scenarios were considerably biased. After bias-correction, the deviations between estimated and actual parameter values were (11.2 ± 6.4) % (vs. (105 ± 21) % without correction) for the flow, (3.6 ± 6.1) % for the permeability-surface area product, (5.8 ± 4.9) % for the vascular volume and (2.5 ± 4.1) % for the interstitial volume; with individual deviations of more than 20% being the exception and just marginal. Increasing the duration of CA administration only had a statistically significant but opposite effect on the accuracy of the estimated flow (declined) and intravascular volume (improved). Physiologically well-defined tissue parameters are structurally identifiable and accurately estimable from DCE data by the conceptually modified two-compartment model in combination with the bias correction. The accuracy of the bias-corrected flow is nearly comparable to that of the three other (theoretically unbiased) model parameters. As compared to conventional two-compartment modeling, this feature constitutes a major advantage for tracer kinetic analysis of both preclinical and clinical DCE imaging studies. © 2017 American Association of Physicists in Medicine.
NASA Astrophysics Data System (ADS)
Eum, H. I.; Cannon, A. J.
2015-12-01
Climate models are a key provider to investigate impacts of projected future climate conditions on regional hydrologic systems. However, there is a considerable mismatch of spatial resolution between GCMs and regional applications, in particular a region characterized by complex terrain such as Korean peninsula. Therefore, a downscaling procedure is an essential to assess regional impacts of climate change. Numerous statistical downscaling methods have been used mainly due to the computational efficiency and simplicity. In this study, four statistical downscaling methods [Bias-Correction/Spatial Disaggregation (BCSD), Bias-Correction/Constructed Analogue (BCCA), Multivariate Adaptive Constructed Analogs (MACA), and Bias-Correction/Climate Imprint (BCCI)] are applied to downscale the latest Climate Forecast System Reanalysis data to stations for precipitation, maximum temperature, and minimum temperature over South Korea. By split sampling scheme, all methods are calibrated with observational station data for 19 years from 1973 to 1991 are and tested for the recent 19 years from 1992 to 2010. To assess skill of the downscaling methods, we construct a comprehensive suite of performance metrics that measure an ability of reproducing temporal correlation, distribution, spatial correlation, and extreme events. In addition, we employ Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) to identify robust statistical downscaling methods based on the performance metrics for each season. The results show that downscaling skill is considerably affected by the skill of CFSR and all methods lead to large improvements in representing all performance metrics. According to seasonal performance metrics evaluated, when TOPSIS is applied, MACA is identified as the most reliable and robust method for all variables and seasons. Note that such result is derived from CFSR output which is recognized as near perfect climate data in climate studies. Therefore, the ranking of this study may be changed when various GCMs are downscaled and evaluated. Nevertheless, it may be informative for end-users (i.e. modelers or water resources managers) to understand and select more suitable downscaling methods corresponding to priorities on regional applications.
Residual Defect Density in Random Disks Deposits.
Topic, Nikola; Pöschel, Thorsten; Gallas, Jason A C
2015-08-03
We investigate the residual distribution of structural defects in very tall packings of disks deposited randomly in large channels. By performing simulations involving the sedimentation of up to 50 × 10(9) particles we find all deposits to consistently show a non-zero residual density of defects obeying a characteristic power-law as a function of the channel width. This remarkable finding corrects the widespread belief that the density of defects should vanish algebraically with growing height. A non-zero residual density of defects implies a type of long-range spatial order in the packing, as opposed to only local ordering. In addition, we find deposits of particles to involve considerably less randomness than generally presumed.
Differential Deposition for Surface Figure Corrections in Grazing Incidence X-Ray Optics
NASA Technical Reports Server (NTRS)
Ramsey, Brian D.; Kilaru, Kiranmayee; Atkins, Carolyn; Gubarev, Mikhail V.; Broadway, David M.
2015-01-01
Differential deposition corrects the low- and mid- spatial-frequency deviations in the axial figure of Wolter-type grazing incidence X-ray optics. Figure deviations is one of the major contributors to the achievable angular resolution. Minimizing figure errors can significantly improve the imaging quality of X-ray optics. Material of varying thickness is selectively deposited, using DC magnetron sputtering, along the length of optic to minimize figure deviations. Custom vacuum chambers are built that can incorporate full-shell and segmented Xray optics. Metrology data of preliminary corrections on a single meridian of full-shell x-ray optics show an improvement of mid-spatial frequencies from 6.7 to 1.8 arc secs HPD. Efforts are in progress to correct a full-shell and segmented optics and to verify angular-resolution improvement with X-ray testing.
Dutton, Daniel J; McLaren, Lindsay
2014-05-06
National data on body mass index (BMI), computed from self-reported height and weight, is readily available for many populations including the Canadian population. Because self-reported weight is found to be systematically under-reported, it has been proposed that the bias in self-reported BMI can be corrected using equations derived from data sets which include both self-reported and measured height and weight. Such correction equations have been developed and adopted. We aim to evaluate the usefulness (i.e., distributional similarity; sensitivity and specificity; and predictive utility vis-à-vis disease outcomes) of existing and new correction equations in population-based research. The Canadian Community Health Surveys from 2005 and 2008 include both measured and self-reported values of height and weight, which allows for construction and evaluation of correction equations. We focused on adults age 18-65, and compared three correction equations (two correcting weight only, and one correcting BMI) against self-reported and measured BMI. We first compared population distributions of BMI. Second, we compared the sensitivity and specificity of self-reported BMI and corrected BMI against measured BMI. Third, we compared the self-reported and corrected BMI in terms of association with health outcomes using logistic regression. All corrections outperformed self-report when estimating the full BMI distribution; the weight-only correction outperformed the BMI-only correction for females in the 23-28 kg/m2 BMI range. In terms of sensitivity/specificity, when estimating obesity prevalence, corrected values of BMI (from any equation) were superior to self-report. In terms of modelling BMI-disease outcome associations, findings were mixed, with no correction proving consistently superior to self-report. If researchers are interested in modelling the full population distribution of BMI, or estimating the prevalence of obesity in a population, then a correction of any kind included in this study is recommended. If the researcher is interested in using BMI as a predictor variable for modelling disease, then both self-reported and corrected BMI result in biased estimates of association.
NASA Astrophysics Data System (ADS)
Feigin, A. M.; Mukhin, D.; Volodin, E. M.; Gavrilov, A.; Loskutov, E. M.
2013-12-01
The new method of decomposition of the Earth's climate system into well separated spatial-temporal patterns ('climatic modes') is discussed. The method is based on: (i) generalization of the MSSA (Multichannel Singular Spectral Analysis) [1] for expanding vector (space-distributed) time series in basis of spatial-temporal empirical orthogonal functions (STEOF), which makes allowance delayed correlations of the processes recorded in spatially separated points; (ii) expanding both real SST data, and longer by several times SST data generated numerically, in STEOF basis; (iii) use of the numerically produced STEOF basis for exclusion of 'too slow' (and thus not represented correctly) processes from real data. The application of the method allows by means of vector time series generated numerically by the INM RAS Coupled Climate Model [2] to separate from real SST anomalies data [3] two climatic modes possessing by noticeably different time scales: 3-5 and 9-11 years. Relations of separated modes to ENSO and PDO are investigated. Possible applications of spatial-temporal climatic patterns concept to prognosis of climate system evolution is discussed. 1. Ghil, M., R. M. Allen, M. D. Dettinger, K. Ide, D. Kondrashov, et al. (2002) "Advanced spectral methods for climatic time series", Rev. Geophys. 40(1), 3.1-3.41. 2. http://83.149.207.89/GCM_DATA_PLOTTING/GCM_INM_DATA_XY_en.htm 3. http://iridl.ldeo.columbia.edu/SOURCES/.KAPLAN/.EXTENDED/.v2/.ssta/
Human short-term spatial memory: precision predicts capacity.
Banta Lavenex, Pamela; Boujon, Valérie; Ndarugendamwo, Angélique; Lavenex, Pierre
2015-03-01
Here, we aimed to determine the capacity of human short-term memory for allocentric spatial information in a real-world setting. Young adults were tested on their ability to learn, on a trial-unique basis, and remember over a 1-min interval the location(s) of 1, 3, 5, or 7 illuminating pads, among 23 pads distributed in a 4m×4m arena surrounded by curtains on three sides. Participants had to walk to and touch the pads with their foot to illuminate the goal locations. In contrast to the predictions from classical slot models of working memory capacity limited to a fixed number of items, i.e., Miller's magical number 7 or Cowan's magical number 4, we found that the number of visited locations to find the goals was consistently about 1.6 times the number of goals, whereas the number of correct choices before erring and the number of errorless trials varied with memory load even when memory load was below the hypothetical memory capacity. In contrast to resource models of visual working memory, we found no evidence that memory resources were evenly distributed among unlimited numbers of items to be remembered. Instead, we found that memory for even one individual location was imprecise, and that memory performance for one location could be used to predict memory performance for multiple locations. Our findings are consistent with a theoretical model suggesting that the precision of the memory for individual locations might determine the capacity of human short-term memory for spatial information. Copyright © 2015 Elsevier Inc. All rights reserved.
O'Brien, Jeremy T; Williams, Evan R; Holman, Hoi-Ying N
2015-03-03
A new experimental setup for spatially resolved ambient infrared laser ablation-mass spectrometry (AIRLAB-MS) that uses an infrared microscope with an infinity-corrected reflective objective and a continuous flow solvent probe coupled to a Fourier transform ion cyclotron resonance mass spectrometer is described. The efficiency of material transfer from the sample to the electrospray ionization emitter was determined using glycerol/methanol droplets containing 1 mM nicotine and is ∼50%. This transfer efficiency is significantly higher than values reported for similar techniques. Laser desorption does not induce fragmentation of biomolecules in droplets containing bradykinin, leucine enkephalin and myoglobin, but loss of the heme group from myoglobin occurs as a result of the denaturing solution used. An application of AIRLAB-MS to biological materials is demonstrated for tobacco leaves. Chemical components are identified from the spatially resolved mass spectra of the ablated plant material, including nicotine and uridine. The reproducibility of measurements made using AIRLAB-MS on plant material was demonstrated by the ablation of six closely spaced areas (within 2 × 2 mm) on a young tobacco leaf, and the results indicate a standard deviation of <10% in the uridine signal obtained for each area. The spatial distribution of nicotine was measured for selected leaf areas and variation in the relative nicotine levels (15-100%) was observed. Comparative analysis of the nicotine distribution was demonstrated for two tobacco plant varieties, a genetically modified plant and its corresponding wild-type, indicating generally higher nicotine levels in the mutant.
Deane, David C; Nicol, Jason M; Gehrig, Susan L; Harding, Claire; Aldridge, Kane T; Goodman, Abigail M; Brookes, Justin D
2017-06-01
Human use of water resources threatens environmental water supplies. If resource managers are to develop policies that avoid unacceptable ecological impacts, some means to predict ecosystem response to changes in water availability is necessary. This is difficult to achieve at spatial scales relevant for water resource management because of the high natural variability in ecosystem hydrology and ecology. Water plant functional groups classify species with similar hydrological niche preferences together, allowing a qualitative means to generalize community responses to changes in hydrology. We tested the potential for functional groups in making quantitative prediction of water plant functional group distributions across diverse wetland types over a large geographical extent. We sampled wetlands covering a broad range of hydrogeomorphic and salinity conditions in South Australia, collecting both hydrological and floristic data from 687 quadrats across 28 wetland hydrological gradients. We built hydrological-niche models for eight water plant functional groups using a range of candidate models combining different surface inundation metrics. We then tested the predictive performance of top-ranked individual and averaged models for each functional group. Cross validation showed that models achieved acceptable predictive performance, with correct classification rates in the range 0.68-0.95. Model predictions can be made at any spatial scale that hydrological data are available and could be implemented in a geographical information system. We show the response of water plant functional groups to inundation is consistent enough across diverse wetland types to quantify the probability of hydrological impacts over regional spatial scales. © 2017 by the Ecological Society of America.
Characterization of Mars' seasonal caps using neutron spectroscopy
Prettyman, T.H.; Feldman, W.C.; Titus, T.N.
2009-01-01
Mars' seasonal caps are characterized during Mars years 26 and 27 (April 2002 to January 2006) using data acquired by the 2001 Mars Odyssey Neutron Spectrometer. Time-dependent maps of the column abundance of seasonal CO 2 surface ice poleward of 60?? latitude in both hemispheres are determined from spatially deconvolved, epithermal neutron counting data. Sources of systematic error are analyzed, including spatial blurring by the spectrometer's broad footprint and the seasonal variations in the abundance of noncondensable gas at high southern latitudes, which are found to be consistent with results reported by Sprague et al. (2004, 2007). Corrections for spatial blurring are found to be important during the recession, when the column abundance of seasonal CO2 ice has the largest latitude gradient. The measured distribution and inventory of seasonal CO2 ice is compared to simulations by a general circulation model (GCM) calibrated using Viking lander pressure data, cap edge functions determined by thermal emission spectroscopy, and other nuclear spectroscopy data sets. On the basis of the amount of CO2 cycled through the caps during years 26 and 27, the gross polar energy balance has not changed significantly since Viking. The distribution of seasonal CO2 ice is longitudinally asymmetric: in the north, deposition rates of CO2 ice are elevated in Acidalia, which is exposed to katabatic winds from Chasma Borealis; in the south, CO2 deposition is highest near the residual cap. During southern recession, CO 2 ice is present longer than calculated by the GCM, which has implications for the local polar energy balance. Copyright 2009 by the American Geophysical Union.
Percolation of fracture networks and stereology
NASA Astrophysics Data System (ADS)
Thovert, Jean-Francois; Mourzenko, Valeri; Adler, Pierre
2017-04-01
The overall properties of fractured porous media depend on the percolative character of the fracture network in a crucial way. The most important examples are permeability and transport. In a recent systematic study, a very wide range of regular, irregular and random fracture shapes is considered, in monodisperse or polydisperse networks containing fractures with different shapes and/or sizes. A simple and new model involving a dimensionless density and a new shape factor is proposed for the percolation threshold, which accounts very efficiently for the influence of the fracture shape. It applies with very good accuracy to monodisperse or moderately polydisperse networks, and provides a good first estimation in other situations. A polydispersity index is shown to control the need for a correction, and the corrective term is modelled for the investigated size distributions. Moreover, and this is crucial for practical applications, the relevant quantities which are present in the expression of the percolation threshold can all be determined from trace maps. An exact and complete set of relations can be derived when the fractures are assumed to be Identical, Isotropically Oriented and Uniformly Distributed (I2OUD). Therefore, the dimensionless density of such networks can be derived directly from the trace maps and its percolating character can be a priori predicted. These relations involve the first five moments of the trace lengths. It is clear that the higher order moments are sensitive to truncation due to the boundaries of the sampling domain. However, it can be shown that the truncation effect can be fully taken into account and corrected, for any fracture shape, size and orientation distributions, if the fractures are spatially uniformly distributed. Systematic applications of these results are made to real fracture networks that we previously analyzed by other means and to numerically simulated networks. It is important to know if the stereological results and their applications can be extended to networks which are not I2OUD. In other words, for a given trace map, an equivalent I2OUD network is defined whose percolating character and permeability are readily deduced. The conditions under which these predicted properties are not too far from the real properties are under investigation.
NASA Astrophysics Data System (ADS)
Son, Geunsoo; Kim, Dongsu; Kim, YoungDo; Lyu, Siwan; Kim, Seojun
2017-04-01
River confluences are zones where two rivers with different geomorphic and hydraulic characteristics amalgamate, resulting in rapid change in terms of flow regime, sediment entrainment and hydraulic geometry. In these confluence zones, the flow structure is basically complicated responded with concurrent mixing of physical and chemical aquatic properties, and continuous channel morphology could be changed due to erosion and sedimentation. In addition, the confluences are regions in which two rivers join and play an important role in river ecology. In order to characterize the mixing process of confluence for understanding the impacts of a river on the other river, therefore, it has been crucial to analyze the spatial mixing patterns for main streams depending on various inflow conditions of tributaries. However, most conventional studies have mostly relied upon hydraulic or water quality numerical models for understanding mixing pattern analysis of confluences, due to the difficulties to acquire a wide spatial range of in-situ data especially for characterizing this kind of mixing process. Even with intensive in-situ measurements, those researches tended to focus mainly on the hydraulic characteristics such as the flow and morphological complexity of confluence, so that very few studies comprehensively included sediment variation with flow at the same time. In this study, subsequently, flow and sediment mixing characteristics were concurrently investigated in the confluence between Nakdong and Nam river in South Korea, where it has been frequently questioned to determine how Nam river affects Nakdong river that recently have suffered various environmental problems such as green algae bloom and erosion/deposition in the confluence. We basically examined the mixing characteristics of confluence by using acoustic Doppler current profilers (ADCPs) which were used to measure hydraulic factors such as flow rate and depth, as well as measuring the suspended sediment concentration by using acoustic backscatter. Cross-sectional ADCP measurements in a confluence were collected with high spatial resolution in order to analyze the details of spatial distribution in the perspective of the three-dimensional mixing patterns of flow and sediment, where backscatters (or SNR) measured from ADCPs were used to track sediment mixing assuming that it could be a surrogate to estimate the suspended sediment concentration. Raw backscatter data were corrected by considering the beam spreading and absorption by water. Also, an optical Laser diffraction instrument (LISST) was used to verify the method of acoustic backscatter and to collect the particle size distribution of main stream and tributary. In addition, image-based spatial distributions of sediment mixture in the confluence were monitored in various flow conditions by using an unmanned aerial vehicle (UAV), which were compared with the spatial distribution of acoustic backscatter. As results, we found that when acoustic backscatter and flow measurements by ADCPs were well processed, they could be proper indicators to identify the spatial patterns of the three-dimensional mixing process between two rivers.
NASA Astrophysics Data System (ADS)
Messenzehl, Karoline; Meyer, Hanna; Otto, Jan-Christoph; Hoffmann, Thomas; Dikau, Richard
2017-06-01
In mountain geosystems, rockfalls are among the most effective sediment transfer processes, reflected in the regional-scale distribution of talus slopes. However, the understanding of the key controlling factors seems to decrease with increasing spatial scale, due to emergent and complex system behavior and not least to recent methodological shortcomings in rockfall modeling research. In this study, we aim (i) to develop a new approach to identify major regional-scale rockfall controls and (ii) to quantify the relative importance of these controls. Using a talus slope inventory in the Turtmann Valley (Swiss Alps), we applied for the first time the decision-tree based random forest algorithm (RF) in combination with a principal component logistic regression (PCLR) to evaluate the spatial distribution of rockfall activity. This study presents new insights into the discussion on whether periglacial rockfall events are controlled more by topo-climatic, cryospheric, paraglacial or/and rock mechanical properties. Both models explain the spatial rockfall pattern very well, given the high areas under the Receiver Operating Characteristic (ROC) curves of > 0.83. Highest accuracy was obtained by the RF, correctly predicting 88% of the rockfall source areas. The RF appears to have a great potential in geomorphic research involving multicollinear data. The regional permafrost distribution, coupled to the bedrock curvature and valley topography, was detected to be the primary rockfall control. Rockfall source areas cluster within a low-radiation elevation belt (2900-3300 m a.s.l,) consistent with a permafrost probability of > 90%. The second most important factor is the time since deglaciation, reflected by the high abundance of rockfalls along recently deglaciated (< 100 years), north-facing slopes. However, our findings also indicate a strong rock mechanical control on the paraglacial rockfall activity, declining either exponentially or linearly since deglaciation. The study demonstrates the benefit of combined statistical approaches for predicting rockfall activity in deglaciated, permafrost-affected mountain valleys and highlights the complex interplay between rock mechanical, paraglacial and topo-climatic controls at the regional scale.
Rusk, Andria; Highfield, Linda; Wilkerson, J Michael; Harrell, Melissa; Obala, Andrew; Amick, Benjamin
2016-02-19
Efforts to improve malaria case management in sub-Saharan Africa have shifted focus to private antimalarial retailers to increase access to appropriate treatment. Demands to decrease intervention cost while increasing efficacy requires interventions tailored to geographic regions with demonstrated need. Cluster analysis presents an opportunity to meet this demand, but has not been applied to the retail sector or antimalarial retailer behaviors. This research conducted cluster analysis on medicine retailer behaviors in Kenya, to improve malaria case management and inform future interventions. Ninety-seven surveys were collected from medicine retailers working in the Webuye Health and Demographic Surveillance Site. Survey items included retailer training, education, antimalarial drug knowledge, recommending behavior, sales, and shop characteristics, and were analyzed using Kulldorff's spatial scan statistic. The Bernoulli purely spatial model for binomial data was used, comparing cases to controls. Statistical significance of found clusters was tested with a likelihood ratio test, using the null hypothesis of no clustering, and a p value based on 999 Monte Carlo simulations. The null hypothesis was rejected with p values of 0.05 or less. A statistically significant cluster of fewer than expected pharmacy-trained retailers was found (RR = .09, p = .001) when compared to the expected random distribution. Drug recommending behavior also yielded a statistically significant cluster, with fewer than expected retailers recommending the correct antimalarial medication to adults (RR = .018, p = .01), and fewer than expected shops selling that medication more often than outdated antimalarials when compared to random distribution (RR = 0.23, p = .007). All three of these clusters were co-located, overlapping in the northwest of the study area. Spatial clustering was found in the data. A concerning amount of correlation was found in one specific region in the study area where multiple behaviors converged in space, highlighting a prime target for interventions. These results also demonstrate the utility of applying geospatial methods in the study of medicine retailer behaviors, making the case for expanding this approach to other regions.
Singer, Annabelle C.; Carr, Margaret F.; Karlsson, Mattias P.; Frank, Loren M.
2013-01-01
SUMMARY The hippocampus frequently replays memories of past experiences during sharp-wave ripple (SWR) events. These events can represent spatial trajectories extending from the animal’s current location to distant locations, suggesting a role in the evaluation of upcoming choices. While SWRs have been linked to learning and memory, the specific role of awake replay remains unclear. Here we show that there is greater coordinated neural activity during SWRs preceding correct, as compared to incorrect, trials in a spatial alternation task. As a result, the proportion of cell pairs coactive during SWRs was predictive of subsequent correct or incorrect responses on a trial-by-trial basis. This effect was seen specifically during early learning, when the hippocampus is essential for task performance. SWR activity preceding correct trials represented multiple trajectories that included both correct and incorrect options. These results suggest that reactivation during awake SWRs contributes to the evaluation of possible choices during memory-guided decision making. PMID:23522050
NASA Astrophysics Data System (ADS)
West, J. B.; Ehleringer, J. R.; Cerling, T.
2006-12-01
Understanding how the biosphere responds to change it at the heart of biogeochemistry, ecology, and other Earth sciences. The dramatic increase in human population and technological capacity over the past 200 years or so has resulted in numerous, simultaneous changes to biosphere structure and function. This, then, has lead to increased urgency in the scientific community to try to understand how systems have already responded to these changes, and how they might do so in the future. Since all biospheric processes exhibit some patchiness or patterns over space, as well as time, we believe that understanding the dynamic interactions between natural systems and human technological manipulations can be improved if these systems are studied in an explicitly spatial context. We present here results of some of our efforts to model the spatial variation in the stable isotope ratios (δ2H and δ18O) of plants over large spatial extents, and how these spatial model predictions compare to spatially explicit data. Stable isotopes trace and record ecological processes and as such, if modeled correctly over Earth's surface allow us insights into changes in biosphere states and processes across spatial scales. The data-model comparisons show good agreement, in spite of the remaining uncertainties (e.g., plant source water isotopic composition). For example, inter-annual changes in climate are recorded in wine stable isotope ratios. Also, a much simpler model of leaf water enrichment driven with spatially continuous global rasters of precipitation and climate normals largely agrees with complex GCM modeling that includes leaf water δ18O. Our results suggest that modeling plant stable isotope ratios across large spatial extents may be done with reasonable accuracy, including over time. These spatial maps, or isoscapes, can now be utilized to help understand spatially distributed data, as well as to help guide future studies designed to understand ecological change across landscapes.
NASA Astrophysics Data System (ADS)
Ghasemi, A.; Borhani, S.; Viparelli, E.; Hill, K. M.
2017-12-01
The Exner equation provides a formal mathematical link between sediment transport and bed morphology. It is typically represented in a discrete formulation where there is a sharp geometric interface between the bedload layer and the bed, below which no particles are entrained. For high temporally and spatially resolved models, this is strictly correct, but typically this is applied in such a way that spatial and temporal fluctuations in the bed surface (bedforms and otherwise) are not captured. This limits the extent to which the exchange between particles in transport and the sediment bed are properly represented, particularly problematic for mixed grain size distributions that exhibit segregation. Nearly two decades ago, Parker (2000) provided a framework for a solution to this dilemma in the form of a probabilistic Exner equation, partially experimentally validated by Wong et al. (2007). We present a computational study designed to develop a physics-based framework for understanding the interplay between physical parameters of the bed and flow and parameters in the Parker (2000) probabilistic formulation. To do so we use Discrete Element Method simulations to relate local time-varying parameters to long-term macroscopic parameters. These include relating local grain size distribution and particle entrainment and deposition rates to long- average bed shear stress and the standard deviation of bed height variations. While relatively simple, these simulations reproduce long-accepted empirically determined transport behaviors such as the Meyer-Peter and Muller (1948) relationship. We also find that these simulations reproduce statistical relationships proposed by Wong et al. (2007) such as a Gaussian distribution of bed heights whose standard deviation increases with increasing bed shear stress. We demonstrate how the ensuing probabilistic formulations provide insight into the transport and deposition of both narrow and wide grain size distribution.
TRMM rainfall estimative coupled with Bell (1969) methodology for extreme rainfall characterization
NASA Astrophysics Data System (ADS)
Schiavo Bernardi, E.; Allasia, D.; Basso, R.; Freitas Ferreira, P.; Tassi, R.
2015-06-01
The lack of rainfall data in Brazil, and, in particular, in Rio Grande do Sul State (RS), hinders the understanding of the spatial and temporal distribution of rainfall, especially in the case of the more complex extreme events. In this context, rainfall's estimation from remote sensors is seen as alternative to the scarcity of rainfall gauges. However, as they are indirect measures, such estimates needs validation. This paper aims to verify the applicability of the Tropical Rainfall Measuring Mission (TRMM) satellite information for extreme rainfall determination in RS. The analysis was accomplished at different temporal scales that ranged from 5 min to daily rainfall while spatial distribution of rainfall was investigated by means of regionalization. An initial test verified TRMM rainfall estimative against measured rainfall at gauges for 1998-2013 period considering different durations and return periods (RP). Results indicated that, for the RP of 2, 5, 10 and 15 years, TRMM overestimated on average 24.7% daily rainfall. As TRMM minimum time-steps is 3 h, in order to verify shorter duration rainfall, the TRMM data were adapted to fit Bell's (1969) generalized IDF formula (based on the existence of similarity between the mechanisms of extreme rainfall events as they are associated to convective cells). Bell`s equation error against measured precipitation was around 5-10%, which varied based on location, RP and duration while the coupled BELL+TRMM error was around 10-35%. However, errors were regionally distributed, allowing a correction to be implemented that reduced by half these values. These findings in turn permitted the use of TRMM+Bell estimates to improve the understanding of spatiotemporal distribution of extreme hydrological rainfall events.
Can single molecule localization microscopy be used to map closely spaced RGD nanodomains?
Nicovich, Philip R.; Soeriyadi, Alexander; Nieves, Daniel J.; Gooding, J. Justin; Gaus, Katharina
2017-01-01
Cells sense and respond to nanoscale variations in the distribution of ligands to adhesion receptors. This makes single molecule localization microscopy (SMLM) an attractive tool to map the distribution of ligands on nanopatterned surfaces. We explore the use of SMLM spatial cluster analysis to detect nanodomains of the cell adhesion-stimulating tripeptide arginine-glycine-aspartic acid (RGD). These domains were formed by the phase separation of block copolymers with controllable spacing on the scale of tens of nanometers. We first determined the topology of the block copolymer with atomic force microscopy (AFM) and then imaged the localization of individual RGD peptides with direct stochastic optical reconstruction microscopy (dSTORM). To compare the data, we analyzed the dSTORM data with DBSCAN (density-based spatial clustering application with noise). The ligand distribution and polymer topology are not necessary identical since peptides may attach to the polymer outside the nanodomains and/or coupling and detection of peptides within the nanodomains is incomplete. We therefore performed simulations to explore the extent to which nanodomains could be mapped with dSTORM. We found that successful detection of nanodomains by dSTORM was influenced by the inter-domain spacing and the localization precision of individual fluorophores, and less by non-specific absorption of ligands to the substratum. For example, under our imaging conditions, DBSCAN identification of nanodomains spaced further than 50 nm apart was largely independent of background localisations, while nanodomains spaced closer than 50 nm required a localization precision of ~11 nm to correctly estimate the modal nearest neighbor distance (NDD) between nanodomains. We therefore conclude that SMLM is a promising technique to directly map the distribution and nanoscale organization of ligands and would benefit from an improved localization precision. PMID:28723958
NASA Astrophysics Data System (ADS)
Tamura, K.; Jansen, R. A.; Windhorst, R. A.
2009-12-01
We present a method to estimate and map the two-dimensional distribution of dust extinction in the late-type spiral galaxy NGC 959 from the theoretical and observed flux ratio of optical V and mid-IR (MIR) 3.6 μm images. Our method is applicable to both young and old stellar populations for a range of metallicities, and is not restricted to lines of sight toward star-formation (SF) regions. We explore this method using a pixel-based analysis on images of NGC 959 obtained in the V band at the Vatican Advanced Technology Telescope and at 3.6 μm (L band) with Spitzer/Infrared Array Camera. We present the original and extinction corrected Galaxy Evolution Explorer (GALEX) far-UV (FUV) and near-UV (NUV) images, as well as optical UBVR images of NGC 959. While the dust lanes are not clearly evident at GALEX resolution, our dust map clearly traces the dust that can be seen silhouetted against the galaxy's disk in the high-resolution Hubble Space Telescope (HST) images of NGC 959. The advantages of our method are (1) it only depends on two relatively common broadband images in the optical V band and in the MIR at 3.6 μm (but adding a near-UV band improves its fidelity); and (2) it is able to map the two-dimensional spatial distribution of dust within a galaxy. This powerful tool could be used to measure the detailed distribution of dust extinction within higher redshift galaxies to be observed with, e.g., the Hubble Space Telescope (HST)/WFC3 (optical near-IR) and James Webb Space Telescope (mid-IR), and to distinguish properties of dust within galaxy bulges, spiral arms, and inter-arm regions.
[Spatial distribution pattern of Pontania dolichura larvae and sampling technique].
Zhang, Feng; Chen, Zhijie; Zhang, Shulian; Zhao, Huiyan
2006-03-01
In this paper, the spatial distribution pattern of Pontania dolichura larvae was analyzed with Taylor's power law, Iwao's distribution function, and six aggregation indexes. The results showed that the spatial distribution pattern of P. dolichura larvae was of aggregated, and the basic component of the distribution was individual colony, with the aggregation intensity increased with density. On branches, the aggregation was caused by the adult behavior of laying eggs and the spatial position of leaves, while on leaves, the aggregation was caused by the spatial position of news leaves in spring when m < 2.37, and by the spatial position of news leaves in spring and the behavior of eclosion and laying eggs when m > 2.37. By using the parameters alpha and beta in Iwao's m * -m regression equation, the optimal and sequential sampling numbers were determined.
Fast Magnetotail Reconnection: Challenge to Global MHD Modeling
NASA Astrophysics Data System (ADS)
Kuznetsova, M. M.; Hesse, M.; Rastaetter, L.; Toth, G.; de Zeeuw, D.; Gombosi, T.
2005-05-01
Representation of fast magnetotail reconnection rates during substorm onset is one of the major challenges to global MHD modeling. Our previous comparative study of collisionless magnetic reconnection in GEM Challenge geometry demonstrated that the reconnection rate is controlled by ion nongyrotropic behavior near the reconnection site and that it can be described in terms of nongyrotropic corrections to the magnetic induction equation. To further test the approach we performed MHD simulations with nongyrotropic corrections of forced reconnection for the Newton Challenge setup. As a next step we employ the global MHD code BATSRUS and test different methods to model fast magnetotail reconnection rates by introducing non-ideal corrections to the induction equation in terms of nongyrotropic corrections, spatially localized resistivity, or current dependent resistivity. The BATSRUS adaptive grid structure allows to perform global simulations with spatial resolution near the reconnection site comparable with spatial resolution of local MHD simulations for the Newton Challenge. We select solar wind conditions which drive the accumulation of magnetic field in the tail lobes and subsequent magnetic reconnection and energy release. Testing the ability of global MHD models to describe magnetotail evolution during substroms is one of the elements of science based validation efforts at the Community Coordinated Modeling Center.
NASA Astrophysics Data System (ADS)
Moradi, F.; Khandaker, M. U.; Mahdiraji, G. A.; Ung, N. M.; Bradley, D. A.
2017-11-01
In recent years doped silica fibre thermoluminescent dosimeters (TLD) have been demonstrated to have considerable potential for irradiation applications, benefitting from the available sensitivity, spatial resolution and dynamic dose range, with primary focus being on the needs of medical dosimetry. Present study concerns the dose distribution inside a cylindrically shaped gamma-ray irradiator cavity, with irradiator facilities such as the familiar 60Co versions being popularly used in industrial applications. Quality assurance of the radiation dose distribution inside the irradiation cell of such a device is of central importance in respect of the delivered dose to the irradiated material. Silica fibre TLD dose-rates obtained within a Gammacell-220 irradiator cavity show the existence of non-negligible dose distribution heterogeneity, by up to 20% and 26% in the radial and axial directions respectively, Monte Carlo simulations and available literature providing some support for present findings. In practice, it is evident that there is need to consider making corrections to nominal dose-rates in order to avoid the potential for under-dosing.
Computational study on the behaviors of granular materials under mechanical cycling
DOE Office of Scientific and Technical Information (OSTI.GOV)
Wang, Xiaoliang; Ye, Minyou; Chen, Hongli, E-mail: hlchen1@ustc.edu.cn
2015-11-07
Considering that fusion pebble beds are probably subjected to the cyclic compression excitation in their future applications, we presented a computational study to report the effect of mechanical cycling on the behaviors of granular matter. The correctness of our numerical experiments was confirmed by a comparison with the effective medium theory. Under the cyclic loads, the fast granular compaction was observed to evolve in a stretched exponential law. Besides, the increasing stiffening in packing structure, especially the decreasing moduli pressure dependence due to granular consolidation, was also observed. For the force chains inside the pebble beds, both the internal forcemore » distribution and the spatial distribution of force chains would become increasingly uniform as the external force perturbation proceeded and therefore produced the stress relief on grains. In this case, the originally proposed 3-parameter Mueth function was found to fail to describe the internal force distribution. Thereby, its improved functional form with 4 parameters was proposed here and proved to better fit the data. These findings will provide more detailed information on the pebble beds for the relevant fusion design and analysis.« less
Inner membrane fusion mediates spatial distribution of axonal mitochondria
Yu, Yiyi; Lee, Hao-Chih; Chen, Kuan-Chieh; Suhan, Joseph; Qiu, Minhua; Ba, Qinle; Yang, Ge
2016-01-01
In eukaryotic cells, mitochondria form a dynamic interconnected network to respond to changing needs at different subcellular locations. A fundamental yet unanswered question regarding this network is whether, and if so how, local fusion and fission of individual mitochondria affect their global distribution. To address this question, we developed high-resolution computational image analysis techniques to examine the relations between mitochondrial fusion/fission and spatial distribution within the axon of Drosophila larval neurons. We found that stationary and moving mitochondria underwent fusion and fission regularly but followed different spatial distribution patterns and exhibited different morphology. Disruption of inner membrane fusion by knockdown of dOpa1, Drosophila Optic Atrophy 1, not only increased the spatial density of stationary and moving mitochondria but also changed their spatial distributions and morphology differentially. Knockdown of dOpa1 also impaired axonal transport of mitochondria. But the changed spatial distributions of mitochondria resulted primarily from disruption of inner membrane fusion because knockdown of Milton, a mitochondrial kinesin-1 adapter, caused similar transport velocity impairment but different spatial distributions. Together, our data reveals that stationary mitochondria within the axon interconnect with moving mitochondria through fusion and fission and that local inner membrane fusion between individual mitochondria mediates their global distribution. PMID:26742817
Calibration of the ROSAT HRI Spectral Response
NASA Technical Reports Server (NTRS)
Prestwich, Andrea
1998-01-01
The ROSAT High Resolution Imager has a limited (2-band) spectral response. This spectral capability can give X-ray hardness ratios on spatial scales of 5 arcseconds. The spectral response of the center of the detector was calibrated before the launch of ROSAT, but the gain decreases-with time and also is a function of position on the detector. To complicate matters further, the satellite is "wobbled", possibly moving a source across several spatial gain states. These difficulties have prevented the spectral response of the ROSAT HRI from being used for scientific measurements. We have used Bright Earth data and in-flight calibration sources to map the spatial and temporal gain changes, and written software which will allow ROSAT users to generate a calibrated XSPEC response matrix and hence determine a calibrated hardness ratio. In this report, we describe the calibration procedure and show how to obtain a response matrix. In Section 2 we give an overview of the calibration procedure, in Section 3 we give a summary of HRI spatial and temporal gain variations. Section 4 describes the routines used to determine the gain distribution of a source. In Sections 5 and 6, we describe in detail how the Bright Earth database and calibration sources are used to derive a corrected response matrix for a given observation. Finally, Section 7 describes how to use the software.
Calibration of the ROSAT HRI Spectral Response
NASA Technical Reports Server (NTRS)
Prestwich, Andrea H.; Silverman, John; McDowell, Jonathan; Callanan, Paul; Snowden, Steve
2000-01-01
The ROSAT High Resolution Imager has a limited (2-band) spectral response. This spectral capability can give X-ray hardness ratios on spatial scales of 5 arcseconds. The spectral response of the center of the detector was calibrated before the launch of ROSAT, but the gain decreases with time and also is a function of position on the detector. To complicate matters further, the satellite is 'wobbled', possibly moving a source across several spatial gain states. These difficulties have prevented the spectral response of the ROSAT High Resolution Imager (HRI) from being used for scientific measurements. We have used Bright Earth data and in-flight calibration sources to map the spatial and temporal gain changes, and written software which will allow ROSAT users to generate a calibrated XSPEC (an x ray spectral fitting package) response matrix and hence determine a calibrated hardness ratio. In this report, we describe the calibration procedure and show how to obtain a response matrix. In Section 2 we give an overview of the calibration procedure, in Section 3 we give a summary of HRI spatial and temporal gain variations. Section 4 describes the routines used to determine the gain distribution of a source. In Sections 5 and 6, we describe in detail how, the Bright Earth database and calibration sources are used to derive a corrected response matrix for a given observation. Finally, Section 7 describes how to use the software.
Federal Register 2010, 2011, 2012, 2013, 2014
2012-02-24
... Conservation Program: Energy Conservation Standards for Distribution Transformers; Correction AGENCY: Office of... standards for distribution transformers. It was recently discovered that values in certain tables of the...,'' including distribution transformers. The Energy Policy Act of 1992 (EPACT 1992), Public Law 102-486, amended...
NASA Technical Reports Server (NTRS)
Weissman, David E.; Hristova-Veleva, Svetla; Callahan, Philip
2006-01-01
The opportunity provided by satellite scatterometers to measure ocean surface winds in strong storms and hurricanes is diminished by the errors in the received backscatter (SIGMA-0) caused by the attenuation, scattering and surface roughening produced by heavy rain. Providing a good rain correction is a very challenging problem, particularly at Ku band (13.4 GHz) where rain effects are strong. Corrections to the scatterometer measurements of ocean surface winds can be pursued with either of two different methods: empirical or physical modeling. The latter method is employed in this study because of the availability of near simultaneous and collocated measurements provided by the MIDORI-II suite of instruments. The AMSR was designed to measure atmospheric water-related parameters on a spatial scale comparable to the SeaWinds scatterometer. These quantities can be converted into volumetric attenuation and scattering at the Ku-band frequency of SeaWinds. Optimal estimates of the volume backscatter and attenuation require a knowledge of the three dimensional distribution of reflectivity on a scale comparable to that of the precipitation. Studies selected near the US coastline enable the much higher resolution NEXRAD reflectivity measurements evaluate the AMSR estimates. We are also conducting research into the effects of different beam geometries and nonuniform beamfilling of precipitation within the field-of-view of the AMSR and the scatterometer. Furthermore, both AMSR and NEXRAD estimates of atmospheric correction can be used to produce corrected SIGMA-0s, which are then input to the JPL wind retrieval algorithm.
Wan, Weishi; Yu, Lei; Zhu, Lin; Yang, Xiaodong; Wei, Zheng; Liu, Jefferson Zhe; Feng, Jun; Kunze, Kai; Schaff, Oliver; Tromp, Ruud; Tang, Wen-Xin
2017-03-01
We describe the design and commissioning of a novel aberration-corrected low energy electron microscope (AC-LEEM). A third magnetic prism array (MPA) is added to the standard AC-LEEM with two prism arrays, allowing the incorporation of an ultrafast spin-polarized electron source alongside the standard cold field emission electron source, without degrading spatial resolution. The high degree of symmetries of the AC-LEEM are utilized while we design the electron optics of the ultrafast spin-polarized electron source, so as to minimize the deleterious effect of time broadening, while maintaining full control of electron spin. A spatial resolution of 2nm and temporal resolution of 10ps (ps) are expected in the future time resolved aberration-corrected spin-polarized LEEM (TR-AC-SPLEEM). The commissioning of the three-prism AC-LEEM has been successfully finished with the cold field emission source, with a spatial resolution below 2nm. Copyright © 2017 Elsevier B.V. All rights reserved.
2014-09-01
peak shaving, conducting power factor correction, matching critical load to most efficient distributed resource, and islanding a system during...photovoltaic arrays during islanding, and power factor correction, the implementation of the ESS by itself is likely to prove cost prohibitive. The DOD...These functions include peak shaving, conducting power factor correction, matching critical load to most efficient distributed resource, and islanding a
Metabolic Flexibility as a Major Predictor of Spatial Distribution in Microbial Communities
Carbonero, Franck; Oakley, Brian B.; Purdy, Kevin J.
2014-01-01
A better understand the ecology of microbes and their role in the global ecosystem could be achieved if traditional ecological theories can be applied to microbes. In ecology organisms are defined as specialists or generalists according to the breadth of their niche. Spatial distribution is often used as a proxy measure of niche breadth; generalists have broad niches and a wide spatial distribution and specialists a narrow niche and spatial distribution. Previous studies suggest that microbial distribution patterns are contrary to this idea; a microbial generalist genus (Desulfobulbus) has a limited spatial distribution while a specialist genus (Methanosaeta) has a cosmopolitan distribution. Therefore, we hypothesise that this counter-intuitive distribution within generalist and specialist microbial genera is a common microbial characteristic. Using molecular fingerprinting the distribution of four microbial genera, two generalists, Desulfobulbus and the methanogenic archaea Methanosarcina, and two specialists, Methanosaeta and the sulfate-reducing bacteria Desulfobacter were analysed in sediment samples from along a UK estuary. Detected genotypes of both generalist genera showed a distinct spatial distribution, significantly correlated with geographic distance between sites. Genotypes of both specialist genera showed no significant differential spatial distribution. These data support the hypothesis that the spatial distribution of specialist and generalist microbes does not match that seen with specialist and generalist large organisms. It may be that generalist microbes, while having a wider potential niche, are constrained, possibly by intrageneric competition, to exploit only a small part of that potential niche while specialists, with far fewer constraints to their niche, are more capable of filling their potential niche more effectively, perhaps by avoiding intrageneric competition. We suggest that these counter-intuitive distribution patterns may be a common feature of microbes in general and represent a distinct microbial principle in ecology, which is a real challenge if we are to develop a truly inclusive ecology. PMID:24465487
NASA Astrophysics Data System (ADS)
Mueller, Dirk; Triebel, Wolfgang; Bochmann, Arne; Schmidl, Gabriele; Eckardt, Daniel; Burkert, Alfons; Roeper, Juergen; Schwerin, Malte
2003-11-01
Concentration profiles of OH, O2 and NO as well as temperature fields in diffusion flames of a length of approx. 300 mm and 40 mm in diameter used for gas-phase synthesis of fused silica have been determined by Planar Laser Induced Fluorescence (PLIF). The measurements have been carried out using a tunable spectrally narrowed KrF laser, whose wavelengths could be switched pulse-to-pulse. The laser beam was shaped as a light sheet into the flame at a fixed position. The flame area under investigation was monitored by moving the burner mounted on a stepper motor. By adapted synchronization the laser induced fluorescence was continuously recorded over the height of the flame perpendicular to the laser light sheet with an intensified CCD camera (10 fps, 8 bit dynamic range, 768 x 576 pixels). By image processing the spatial offset between images was corrected and superposed images were averaged and analyzed. This method allows to investigate the flame by recording 2D-fluorescence images including an automatic correction of intensity inhomogeneities of the laser light sheet. Based on the excited radical or molecule the fluorescence images were used to determine concentration and temperature distributions to build up a 2D-map of the flame. The PLIF experiment was calibrated with precise determination of the temperature at one coordinate of the flame by Spontaneous Vibrational Raman Scattering (VRS) of N2. As a result temperatures up to 3200 K could be determined with an accuracy better than 3% and a spatial resolution better than 1 mm. Temperature variations in the flame at different gas flows of fuel and oxidizer could be monitored sensitively. Also, the influence of different carrier gases like N2, Ar and He on the temperature distribution was investigated. Fluctuations in gas flow caused by turbulence could be monitored as well.
Wang, Peng; Yin, Lingshu; Zhang, Yawei; Kirk, Maura; Song, Gang; Ahn, Peter H; Lin, Alexander; Gee, James; Dolney, Derek; Solberg, Timothy D; Maughan, Richard; McDonough, James; Teo, Boon-Keng Kevin
2016-03-08
The aim of this work is to demonstrate the feasibility of using water-equivalent thickness (WET) and virtual proton depth radiographs (PDRs) of intensity corrected cone-beam computed tomography (CBCT) to detect anatomical change and patient setup error to trigger adaptive head and neck proton therapy. The planning CT (pCT) and linear accelerator (linac) equipped CBCTs acquired weekly during treatment of a head and neck patient were used in this study. Deformable image registration (DIR) was used to register each CBCT with the pCT and map Hounsfield units (HUs) from the planning CT (pCT) onto the daily CBCT. The deformed pCT is referred as the corrected CBCT (cCBCT). Two dimensional virtual lateral PDRs were generated using a ray-tracing technique to project the cumulative WET from a virtual source through the cCBCT and the pCT onto a virtual plane. The PDRs were used to identify anatomic regions with large variations in the proton range between the cCBCT and pCT using a threshold of 3 mm relative difference of WET and 3 mm search radius criteria. The relationship between PDR differences and dose distribution is established. Due to weight change and tumor response during treatment, large variations in WETs were observed in the relative PDRs which corresponded spatially with an increase in the number of failing points within the GTV, especially in the pharynx area. Failing points were also evident near the posterior neck due to setup variations. Differences in PDRs correlated spatially to differences in the distal dose distribution in the beam's eye view. Virtual PDRs generated from volumetric data, such as pCTs or CBCTs, are potentially a useful quantitative tool in proton therapy. PDRs and WET analysis may be used to detect anatomical change from baseline during treatment and trigger further analysis in adaptive proton therapy.
MSWEP V2 global 3-hourly 0.1° precipitation: methodology and quantitative appraisal
NASA Astrophysics Data System (ADS)
Beck, H.; Yang, L.; Pan, M.; Wood, E. F.; William, L.
2017-12-01
Here, we present Multi-Source Weighted-Ensemble Precipitation (MSWEP) V2, the first fully global gridded precipitation (P) dataset with a 0.1° spatial resolution. The dataset covers the period 1979-2016, has a 3-hourly temporal resolution, and was derived by optimally merging a wide range of data sources based on gauges (WorldClim, GHCN-D, GSOD, and others), satellites (CMORPH, GridSat, GSMaP, and TMPA 3B42RT), and reanalyses (ERA-Interim, JRA-55, and NCEP-CFSR). MSWEP V2 implements some major improvements over V1, such as (i) the correction of distributional P biases using cumulative distribution function matching, (ii) increasing the spatial resolution from 0.25° to 0.1°, (iii) the inclusion of ocean areas, (iv) the addition of NCEP-CFSR P estimates, (v) the addition of thermal infrared-based P estimates for the pre-TRMM era, (vi) the addition of 0.1° daily interpolated gauge data, (vii) the use of a daily gauge correction scheme that accounts for regional differences in the 24-hour accumulation period of gauges, and (viii) extension of the data record to 2016. The gauge-based assessment of the reanalysis and satellite P datasets, necessary for establishing the merging weights, revealed that the reanalysis datasets strongly overestimate the P frequency for the entire globe, and that the satellite (resp. reanalysis) datasets consistently performed better at low (high) latitudes. Compared to other state-of-the-art P datasets, MSWEP V2 exhibits more plausible global patterns in mean annual P, percentiles, and annual number of dry days, and better resolves the small-scale variability over topographically complex terrain. Other P datasets appear to consistently underestimate P amounts over mountainous regions. Long-term mean P estimates for the global, land, and ocean domains based on MSWEP V2 are 959, 796, and 1026 mm/yr, respectively, in close agreement with the best previous published estimates.
The spatial distribution of cropland carbon transfer in Jilin province during 2014
NASA Astrophysics Data System (ADS)
Cai, Xintong; Meng, Jian; Li, Qiuhui; Gao, Shuang; Zhu, Xianjin
2018-01-01
Cropland carbon transfer (CCT, gC yr-1) is an important component in the carbon budget of terrestrial ecosystems. Analyzing the value of CCT and its spatial variation would provide a data basis for assessing the regional carbon balance. Based on the data from Jilin statistical yearbook 2015, we investigated the spatial variation of CCT in Jilin province during 2014. Results suggest that the CCT of Jilin province was 30.83 TgC, which exhibited a decreasing trend from the centre to the border but the west side was higher than the east. The magnitude of carbon transfer per area (MCT), which showed a similar spatial distribution with CCT, was the dominating component of CCT spatial distribution. The spatial distribution of MCT was jointly affected by that of the ratio of planting area to regional area (RPR) and carbon transfer per planting area (CTP), where RPR and CTP contributed 65.55% and 34.5% of MCT spatial distribution, respectively. Therefore, CCT in Jilin province spatially varied, which made it highly needed to consider the difference in CCT among regions when we assessing the regional carbon budget.
Adaptive optics system performance approximations for atmospheric turbulence correction
NASA Astrophysics Data System (ADS)
Tyson, Robert K.
1990-10-01
Analysis of adaptive optics system behavior often can be reduced to a few approximations and scaling laws. For atmospheric turbulence correction, the deformable mirror (DM) fitting error is most often used to determine a priori the interactuator spacing and the total number of correction zones required. This paper examines the mirror fitting error in terms of its most commonly used exponential form. The explicit constant in the error term is dependent on deformable mirror influence function shape and actuator geometry. The method of least squares fitting of discrete influence functions to the turbulent wavefront is compared to the linear spatial filtering approximation of system performance. It is found that the spatial filtering method overstimates the correctability of the adaptive optics system by a small amount. By evaluating fitting error for a number of DM configurations, actuator geometries, and influence functions, fitting error constants verify some earlier investigations.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Gonzalez-Castano, D. M.; Gonzalez, L. Brualla; Gago-Arias, M. A.
2012-01-15
Purpose: This work contains an alternative methodology for obtaining correction factors for ionization chamber (IC) dosimetry of small fields and composite fields such as IMRT. The method is based on the convolution/superposition (C/S) of an IC response function (RF) with the dose distribution in a certain plane which includes chamber position. This method is an alternative to the full Monte Carlo (MC) approach that has been used previously by many authors for the same objective. Methods: The readout of an IC at a point inside a phantom irradiated by a certain beam can be obtained as the convolution of themore » dose spatial distribution caused by the beam and the IC two-dimensional RF. The proposed methodology has been applied successfully to predict the response of a PTW 30013 IC when measuring different nonreference fields, namely: output factors of 6 MV small fields, beam profiles of cobalt 60 narrow fields and 6 MV radiosurgery segments. The two-dimensional RF of a PTW 30013 IC was obtained by MC simulation of the absorbed dose to cavity air when the IC was scanned by a 0.6 x 0.6 mm{sup 2} cross section parallel pencil beam at low depth in a water phantom. For each of the cases studied, the results of the IC direct measurement were compared with the corresponding obtained by the C/S method. Results: For all of the cases studied, the agreement between the IC direct measurement and the IC calculated response was excellent (better than 1.5%). Conclusions: This method could be implemented in TPS in order to calculate dosimetry correction factors when an experimental IMRT treatment verification with in-phantom ionization chamber is performed. The miss-response of the IC due to the nonreference conditions could be quickly corrected by this method rather than employing MC derived correction factors. This method can be considered as an alternative to the plan-class associated correction factors proposed recently as part of an IAEA work group on nonstandard field dosimetry.« less
2007-09-27
the spatial and spectral resolution ...variety of geological and vegetation mapping efforts, the Hymap sensor offered the best available combination of spectral and spatial resolution , signal... The limitations of the technology currently relate to spatial and spectral resolution and geo- correction accuracy. Secondly, HSI datasets
USDA-ARS?s Scientific Manuscript database
In this paper, we propose approaches to improve the pixel-based support vector machine (SVM) classification for urban land use and land cover (LULC) mapping from airborne hyperspectral imagery with high spatial resolution. Class spatial neighborhood relationship is used to correct the misclassified ...
Head-mounted spatial instruments: Synthetic reality or impossible dream
NASA Technical Reports Server (NTRS)
Ellis, Stephen R.; Grunwald, Arthur; Velger, Mordekhai
1988-01-01
A spatial instrument is defined as a display device which has been either geometrically or symbolically enhanced to better enable a user to accomplish a particular task. Research conducted over the past several years on 3-D spatial instruments has shown that perspective displays, even when viewed from the correct viewpoint, are subject to systematic viewer biases. These biases interfere with correct spatial judgements of the presented pictorial information. It is also found that deliberate, appropriate geometric distortion of the perspective projection of an image can improve user performance. These two findings raise intriguing questions concerning the design of head-mounted spatial instruments. The design of such instruments may not only require the introduction of compensatory distortions to remove the neutrally occurring biases but also may significantly benefit from the introduction of artificial distortions which enhance performance. These image manipulations, however, can cause a loss of visual-vestibular coordination and induce motion sickness. Additionally, adaptation to these manipulations is apt to be impaired by computational delays in the image display. Consequently, the design of head-mounted spatial instruments will require an understanding of the tolerable limits of visual-vestibular discord.
Spatial filtering velocimeter for vehicle navigation with extended measurement range
NASA Astrophysics Data System (ADS)
He, Xin; Zhou, Jian; Nie, Xiaoming; Long, Xingwu
2015-05-01
The idea of using spatial filtering velocimeter is proposed to provide accurate velocity information for vehicle autonomous navigation system. The presented spatial filtering velocimeter is based on a CMOS linear image sensor. The limited frame rate restricts high speed measurement of the vehicle. To extend measurement range of the velocimeter, a method of frequency shifting is put forward. Theoretical analysis shows that the frequency of output signal can be reduced and the measurement range can be doubled by this method when the shifting direction is set the same with that of image velocity. The approach of fast Fourier transform (FFT) is employed to obtain the power spectra of the spatially filtered signals. Because of limited frequency resolution of FFT, a frequency spectrum correction algorithm, called energy centrobaric correction, is used to improve the frequency resolution. The correction accuracy energy centrobaric correction is analyzed. Experiments are carried out to measure the moving surface of a conveyor belt. The experimental results show that the maximum measurable velocity is about 800deg/s without frequency shifting, 1600deg/s with frequency shifting, when the frame rate of the image is about 8117 Hz. Therefore, the measurement range is doubled by the method of frequency shifting. Furthermore, experiments were carried out to measure the vehicle velocity simultaneously using both the designed SFV and a laser Doppler velocimeter (LDV). The measurement results of the presented SFV are coincident with that of the LDV, but with bigger fluctuation. Therefore, it has the potential of application to vehicular autonomous navigation.
NASA Astrophysics Data System (ADS)
Gang, Liu; Meihui, Qu; Guolin, Feng; Qucheng, Chu; Jing, Cao; Jie, Yang; Ling, Cao; Yao, Feng
2018-03-01
This paper introduces three quantitative indicators to conduct research for characterizing Northeast China cold vortex persistence activity: cold vortex persistence, generalized "cold vortex," and cold vortex precipitation. As discussed in the first part of paper, a hindcast is performed by multiple regressions using Northeast China precipitation from 2012 to 2014 combination with the previous winter 144 air-sea system factors. The results show that the mentioned three cold vortex index series can reflect the spatial and temporal distributions of observational precipitation in 2012-2014 and obtain results. The cold vortex factors are then added to the Forecast System on Dynamical and Analogy Skills (FODAS) to carry out dynamic statistical hindcast of precipitation in Northeast China from 2003 to 2012. Based on the characteristics and significance of each index, precipitation hindcast is carried out for Northeast China in May, June, July, August, May-June, and July-August. It turns out that the Northeast Cold Vortex Index Series, as defined in this paper, can make positive corrections to the FODAS forecast system, and most of the index correction results are higher than the system's own correction value. This study provides quantitative index products and supplies a solid technical foundation and support for monthly precipitation forecast in Northeast China.
Grids in topographic maps reduce distortions in the recall of learned object locations.
Edler, Dennis; Bestgen, Anne-Kathrin; Kuchinke, Lars; Dickmann, Frank
2014-01-01
To date, it has been shown that cognitive map representations based on cartographic visualisations are systematically distorted. The grid is a traditional element of map graphics that has rarely been considered in research on perception-based spatial distortions. Grids do not only support the map reader in finding coordinates or locations of objects, they also provide a systematic structure for clustering visual map information ("spatial chunks"). The aim of this study was to examine whether different cartographic kinds of grids reduce spatial distortions and improve recall memory for object locations. Recall performance was measured as both the percentage of correctly recalled objects (hit rate) and the mean distance errors of correctly recalled objects (spatial accuracy). Different kinds of grids (continuous lines, dashed lines, crosses) were applied to topographic maps. These maps were also varied in their type of characteristic areas (LANDSCAPE) and different information layer compositions (DENSITY) to examine the effects of map complexity. The study involving 144 participants shows that all experimental cartographic factors (GRID, LANDSCAPE, DENSITY) improve recall performance and spatial accuracy of learned object locations. Overlaying a topographic map with a grid significantly reduces the mean distance errors of correctly recalled map objects. The paper includes a discussion of a square grid's usefulness concerning object location memory, independent of whether the grid is clearly visible (continuous or dashed lines) or only indicated by crosses.
NASA Astrophysics Data System (ADS)
Cao, Yanpeng; Tisse, Christel-Loic
2013-06-01
In uncooled LWIR microbolometer imaging systems, temperature fluctuations of FPA (Focal Plane Array) as well as lens and mechanical components placed along the optical path result in thermal drift and spatial non-uniformity. These non-idealities generate undesirable FPN (Fixed-Pattern-Noise) that is difficult to remove using traditional, individual shutterless and TEC-less (Thermo-Electric Cooling) techniques. In this paper we introduce a novel single-image based processing approach that marries the benefits of both statistical scene-based and calibration-based NUC algorithms, without relying neither on extra temperature reference nor accurate motion estimation, to compensate the resulting temperature-dependent non-uniformities. Our method includes two subsequent image processing steps. Firstly, an empirical behavioral model is derived by calibrations to characterize the spatio-temporal response of the microbolometric FPA to environmental and scene temperature fluctuations. Secondly, we experimentally establish that the FPN component caused by the optics creates a spatio-temporally continuous, low frequency, low-magnitude variation of the image intensity. We propose to make use of this property and learn a prior on the spatial distribution of natural image gradients to infer the correction function for the entire image. The performance and robustness of the proposed temperature-adaptive NUC method are demonstrated by showing results obtained from a 640×512 pixels uncooled LWIR microbolometer imaging system operating over a broad range of temperature and with rapid environmental temperature changes (i.e. from -5°C to 65°C within 10 minutes).
Unbiased methods for removing systematics from galaxy clustering measurements
NASA Astrophysics Data System (ADS)
Elsner, Franz; Leistedt, Boris; Peiris, Hiranya V.
2016-02-01
Measuring the angular clustering of galaxies as a function of redshift is a powerful method for extracting information from the three-dimensional galaxy distribution. The precision of such measurements will dramatically increase with ongoing and future wide-field galaxy surveys. However, these are also increasingly sensitive to observational and astrophysical contaminants. Here, we study the statistical properties of three methods proposed for controlling such systematics - template subtraction, basic mode projection, and extended mode projection - all of which make use of externally supplied template maps, designed to characterize and capture the spatial variations of potential systematic effects. Based on a detailed mathematical analysis, and in agreement with simulations, we find that the template subtraction method in its original formulation returns biased estimates of the galaxy angular clustering. We derive closed-form expressions that should be used to correct results for this shortcoming. Turning to the basic mode projection algorithm, we prove it to be free of any bias, whereas we conclude that results computed with extended mode projection are biased. Within a simplified setup, we derive analytical expressions for the bias and discuss the options for correcting it in more realistic configurations. Common to all three methods is an increased estimator variance induced by the cleaning process, albeit at different levels. These results enable unbiased high-precision clustering measurements in the presence of spatially varying systematics, an essential step towards realizing the full potential of current and planned galaxy surveys.
Fast flow-based algorithm for creating density-equalizing map projections
Gastner, Michael T.; Seguy, Vivien; More, Pratyush
2018-01-01
Cartograms are maps that rescale geographic regions (e.g., countries, districts) such that their areas are proportional to quantitative demographic data (e.g., population size, gross domestic product). Unlike conventional bar or pie charts, cartograms can represent correctly which regions share common borders, resulting in insightful visualizations that can be the basis for further spatial statistical analysis. Computer programs can assist data scientists in preparing cartograms, but developing an algorithm that can quickly transform every coordinate on the map (including points that are not exactly on a border) while generating recognizable images has remained a challenge. Methods that translate the cartographic deformations into physics-inspired equations of motion have become popular, but solving these equations with sufficient accuracy can still take several minutes on current hardware. Here we introduce a flow-based algorithm whose equations of motion are numerically easier to solve compared with previous methods. The equations allow straightforward parallelization so that the calculation takes only a few seconds even for complex and detailed input. Despite the speedup, the proposed algorithm still keeps the advantages of previous techniques: With comparable quantitative measures of shape distortion, it accurately scales all areas, correctly fits the regions together, and generates a map projection for every point. We demonstrate the use of our algorithm with applications to the 2016 US election results, the gross domestic products of Indian states and Chinese provinces, and the spatial distribution of deaths in the London borough of Kensington and Chelsea between 2011 and 2014. PMID:29463721
Tomographic diagnostic of the hydrogen beam from a negative ion source
NASA Astrophysics Data System (ADS)
Agostini, M.; Brombin, M.; Serianni, G.; Pasqualotto, R.
2011-10-01
In this paper the tomographic diagnostic developed to characterize the 2D density distribution of a particle beam from a negative ion source is described. In particular, the reliability of this diagnostic has been tested by considering the geometry of the source for the production of ions of deuterium extracted from an rf plasma (SPIDER). SPIDER is a low energy prototype negative ion source for the international thermonuclear experimental reactor (ITER) neutral beam injector, aimed at demonstrating the capability to create and extract a current of D- (H-) ions up to 50 A (60 A) accelerated at 100 kV. The ions are extracted over a wide surface (1.52×0.56m2) with a uniform plasma density which is prescribed to remain within 10% of the mean value. The main target of the tomographic diagnostic is the measurement of the beam uniformity with sufficient spatial resolution and of its evolution throughout the pulse duration. To reach this target, a tomographic algorithm based on the simultaneous algebraic reconstruction technique is developed and the geometry of the lines of sight is optimized so as to cover the whole area of the beam. Phantoms that reproduce different experimental beam configurations are simulated and reconstructed, and the role of the noise in the signals is studied. The simulated phantoms are correctly reconstructed and their two-dimensional spatial nonuniformity is correctly estimated, up to a noise level of 10% with respect to the signal.
Veazey, Lindsay M; Franklin, Erik C; Kelley, Christopher; Rooney, John; Frazer, L Neil; Toonen, Robert J
2016-01-01
Predictive habitat suitability models are powerful tools for cost-effective, statistically robust assessment of the environmental drivers of species distributions. The aim of this study was to develop predictive habitat suitability models for two genera of scleractinian corals (Leptoserisand Montipora) found within the mesophotic zone across the main Hawaiian Islands. The mesophotic zone (30-180 m) is challenging to reach, and therefore historically understudied, because it falls between the maximum limit of SCUBA divers and the minimum typical working depth of submersible vehicles. Here, we implement a logistic regression with rare events corrections to account for the scarcity of presence observations within the dataset. These corrections reduced the coefficient error and improved overall prediction success (73.6% and 74.3%) for both original regression models. The final models included depth, rugosity, slope, mean current velocity, and wave height as the best environmental covariates for predicting the occurrence of the two genera in the mesophotic zone. Using an objectively selected theta ("presence") threshold, the predicted presence probability values (average of 0.051 for Leptoseris and 0.040 for Montipora) were translated to spatially-explicit habitat suitability maps of the main Hawaiian Islands at 25 m grid cell resolution. Our maps are the first of their kind to use extant presence and absence data to examine the habitat preferences of these two dominant mesophotic coral genera across Hawai'i.
Naud, Alexandre; Chailleux, Eloise; Kestens, Yan; Bret, Céline; Desjardins, Dominic; Petit, Odile; Ngoubangoye, Barthélémy; Sueur, Cédric
2016-01-01
Although there exist advantages to group-living in comparison to a solitary lifestyle, costs and gains of group-living may be unequally distributed among group members. Predation risk, vigilance levels and food intake may be unevenly distributed across group spatial geometry and certain within-group spatial positions may be more or less advantageous depending on the spatial distribution of these factors. In species characterized with dominance hierarchy, high-ranking individuals are commonly observed in advantageous spatial position. However, in complex social systems, individuals can develop affiliative relationships that may balance the effect of dominance relationships in individual's spatial distribution. The objective of the present study is to investigate how the group spatial distribution of a semi-free ranging colony of Mandrills relates to its social organization. Using spatial observations in an area surrounding the feeding zone, we tested the three following hypothesis: (1) does dominance hierarchy explain being observed in proximity or far from a food patch? (2) Do affiliative associations also explain being observed in proximity or far from a food patch? (3) Do the differences in rank in the group hierarchy explain being co-observed in proximity of a food patch? Our results showed that high-ranking individuals were more observed in proximity of the feeding zone while low-ranking individuals were more observed at the boundaries of the observation area. Furthermore, we observed that affiliative relationships were also associated with individual spatial distributions and explain more of the total variance of the spatial distribution in comparison with dominance hierarchy. Finally, we found that individuals observed at a same moment in proximity of the feeding zone were more likely to be distant in the hierarchy while controlling for maternal kinship, age and sex similarity. This study brings some elements about how affiliative networks and dominance hierarchy are related to spatial positions in primates. PMID:27199845
Naud, Alexandre; Chailleux, Eloise; Kestens, Yan; Bret, Céline; Desjardins, Dominic; Petit, Odile; Ngoubangoye, Barthélémy; Sueur, Cédric
2016-01-01
Although there exist advantages to group-living in comparison to a solitary lifestyle, costs and gains of group-living may be unequally distributed among group members. Predation risk, vigilance levels and food intake may be unevenly distributed across group spatial geometry and certain within-group spatial positions may be more or less advantageous depending on the spatial distribution of these factors. In species characterized with dominance hierarchy, high-ranking individuals are commonly observed in advantageous spatial position. However, in complex social systems, individuals can develop affiliative relationships that may balance the effect of dominance relationships in individual's spatial distribution. The objective of the present study is to investigate how the group spatial distribution of a semi-free ranging colony of Mandrills relates to its social organization. Using spatial observations in an area surrounding the feeding zone, we tested the three following hypothesis: (1) does dominance hierarchy explain being observed in proximity or far from a food patch? (2) Do affiliative associations also explain being observed in proximity or far from a food patch? (3) Do the differences in rank in the group hierarchy explain being co-observed in proximity of a food patch? Our results showed that high-ranking individuals were more observed in proximity of the feeding zone while low-ranking individuals were more observed at the boundaries of the observation area. Furthermore, we observed that affiliative relationships were also associated with individual spatial distributions and explain more of the total variance of the spatial distribution in comparison with dominance hierarchy. Finally, we found that individuals observed at a same moment in proximity of the feeding zone were more likely to be distant in the hierarchy while controlling for maternal kinship, age and sex similarity. This study brings some elements about how affiliative networks and dominance hierarchy are related to spatial positions in primates.
NASA Astrophysics Data System (ADS)
Jansen, Rolf A.; Kim, Duho; Shewcraft, Timothy; Windhorst, Rogier A.; Tamura, Kazuyuki
2015-01-01
Extinction by dust hampers our understanding of galaxies at all redshifts, and is not constant within or across the face of a galaxy, nor from galaxy to galaxy. We presented an empirical method to correct galaxy images for extinction due to interstellar dust on a pixel by pixel basis, using only rest-frame 3.6 and 0.55μm images. While this "βV" method is approximate in nature, in its first applications we revealed hidden coherent galaxy structures like a stellar bar and ridges of dust, while anomalous inferred central extinctions proved powerful tracers of hidden AGN. This method is particularly promising for deep mid-IR imaging surveys with JWST in fields covered by HST in visible light, since their resolutions will be well-matched. Here we report on our follow-up investigation to explore the applicability, robustness, and fidelity of the βV method on linear size scales from pc to kpc and in regions of varying star formation histories, metallicities, and dust content/distribution. We do so by combining WISE 3.4(Spitzer/IRAC 3.6)μm images of the LMC and SMC---the nearest astrophysical laboratories with a range of sub-solar metallicities--- with 2MASS near-IR and OGLE-III multi-year V and I reference images and catalogs. We assess at ~1" (~0.25--0.35pc) resolution the properties of the stellar populations that contribute to the flux in each WISE(IRAC) resolution element using the 2MASS and OGLE-III data. That allows us to measure the observed V-to-3.4(3.6)μm flux ratio per WISE(IRAC) resolution element. Subsequent resampling and PSF-matching at geometrically increasing scales from pc to kpc resolution elements allows us to assess the accuracy and fidelity of the method as a multi-variate function of the resolution, underlying stellar population mixture, physical environments, and projected distribution of dust. A companion poster (D. Kim et al.) discusses the modeling of the inherent flux ratios of composite stellar populations as functions of metallicity and star formation histories. Resulting predicted βV,0 will serve as calibrations for the spatially-resolved extinction correction of galaxies at all redshifts where the method is proved reliable. This work is funded by NASA/ADAP grant NNX12AE47G.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Shi, L; Zhu, L; Vedantham, S
Purpose: Scatter contamination is detrimental to image quality in dedicated cone-beam breast CT (CBBCT), resulting in cupping artifacts and loss of contrast in reconstructed images. Such effects impede visualization of breast lesions and the quantitative accuracy. Previously, we proposed a library-based software approach to suppress scatter on CBBCT images. In this work, we quantify the efficacy and stability of this approach using datasets from 15 human subjects. Methods: A pre-computed scatter library is generated using Monte Carlo simulations for semi-ellipsoid breast models and homogeneous fibroglandular/adipose tissue mixture encompassing the range reported in literature. Projection datasets from 15 human subjects thatmore » cover 95 percentile of breast dimensions and fibroglandular volume fraction were included in the analysis. Our investigations indicate that it is sufficient to consider the breast dimensions alone and variation in fibroglandular fraction does not significantly affect the scatter-to-primary ratio. The breast diameter is measured from a first-pass reconstruction; the appropriate scatter distribution is selected from the library; and, deformed by considering the discrepancy in total projection intensity between the clinical dataset and the simulated semi-ellipsoidal breast. The deformed scatter-distribution is subtracted from the measured projections for scatter correction. Spatial non-uniformity (SNU) and contrast-to-noise ratio (CNR) were used as quantitative metrics to evaluate the results. Results: On the 15 patient cases, our method reduced the overall image spatial non-uniformity (SNU) from 7.14%±2.94% (mean ± standard deviation) to 2.47%±0.68% in coronal view and from 10.14%±4.1% to 3.02% ±1.26% in sagittal view. The average contrast to noise ratio (CNR) improved by a factor of 1.49±0.40 in coronal view and by 2.12±1.54 in sagittal view. Conclusion: We demonstrate the robustness and effectiveness of a library-based scatter correction method using patient datasets with large variability in breast dimensions and composition. The high computational efficiency and simplicity in implementation make this attractive for clinical implementation. Supported partly by NIH R21EB019597, R21CA134128 and R01CA195512.The content is solely the responsibility of the authors and does not necessarily represent the official views of the National Institutes of Health.« less
NASA Astrophysics Data System (ADS)
Arvani, Barbara; Pierce, R. Bradley; Lyapustin, Alexei I.; Wang, Yujie; Ghermandi, Grazia; Teggi, Sergio
2016-09-01
In this work, the new 1 km-resolved Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is employed to characterize seasonal PM10 - AOD correlations over northern Italy. The accuracy of the new dataset is assessed compared to the widely used Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Aerosol Optical Depth (AOD) data, retrieved at 0.55 μm with spatial resolution of 10 km (MYD04_L2). We focused on evaluating the ability of these two products to characterize both temporal and spatial distributions of aerosols within urban and suburban areas. Ground PM10 measurements were obtained from 73 of the Italian Regional Agency for Environmental Protection (ARPA) monitoring stations, spread across northern Italy, during a three-year period from 2010 to 2012. The Po Valley area (northern Italy) was chosen as the study domain because of its severe urban air pollution, resulting from it having the highest population and industrial manufacturing density in the country, being located in a valley where two surrounding mountain chains favor the stagnation of pollutants. We found that the global correlations between the bin-averaged PM10 and AOD are R2 = 0.83 and R2 = 0.44 for MYD04_L2 and for MAIAC, respectively, suggesting a greater sensitivity of the high-resolution product to small-scale deviations. However, the introduction of Relative Humidity (RH) and Planetary Boundary Layer (PBL) depth corrections allowed for a significant improvement to the bin-averaged PM - AOD correlation, which led to a similar performance: R2 = 0.96 for MODIS and R2 = 0.95 for MAIAC. Furthermore, the introduction of the PBL information in the corrected AOD values was found to be crucial in order to capture the clear seasonal cycle shown by measured PM10 values. The study allowed us to define four seasonal linear correlations that estimate PM10 concentrations satisfactorily from the remotely sensed MAIAC AOD retrieval. Overall, the results show that the high resolution provided by MAIAC retrieval data is much more relevant than the 10 km MODIS data to characterize PM10 in this region of Italy which has a pretty limited geographical domain but a broad variety of land usages and consequent particulate concentrations.
NASA Technical Reports Server (NTRS)
Arvani, Barbara; Pierce, R. Bradley; Lyapustin, Alexei I.; Wang, Yujie; Ghermandi, Grazia; Teggi, Sergio
2016-01-01
In this work, the new 1-km-resolved Multi-Angle Implementation of Atmospheric Correction (MAIAC) algorithm is employed to characterize seasonal AOD-PM10 correlations over northern Italy. The accuracy of the new dataset is assessed versus the widely used Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 5.1 Aerosol Optical Depth (AOD) data, retrieved at 0.55 microns with spatial resolution of 10 km (MYD04). We focused on evaluating the ability of these two products to characterize both temporal and spatial distributions of aerosols within urban and suburban areas. Ground PM10 measurements were obtained from 73 of the Italian Regional Agency for Environmental Protection (ARPA) monitoring stations, spread across northern Italy, for a three-year period from 2010 to 2012. The Po Valley area (northern Italy) was chosen as the study domain because of severe urban air pollution, resulting from the highest population and industrial manufacturing density in the country, being located in a valley where two surrounding mountain chains favor the stagnation of pollutants. We found that the global correlations between PM10 and AOD are R(sup 2) = 0.83 and R(sup 2) = 0.44 for MYD04_L2 and for MAIAC, respectively, suggesting for a greater sensitiveness of the high-resolution product to small-scale deviations. However, the introduction of Relative Humidity (RH) and Planetary Boundary Layer (PBL) depth corrections gave a significant improvement to the PM AOD correlation, which led to similar performance: R(sup 2) = 0.96 for MODIS and R(sup 2) = 0.95 for MAIAC. Furthermore, the introduction of the PBL information in the corrected AOD values was found to be crucial in order to capture the clear seasonal cycle shown by measured PM10 values. The study allowed us to define four seasonal linear correlations that estimate PM10 concentrations satisfactorily from the remotely sensed MAIAC AOD retrieval. Overall, the results show that the high resolution provided by MAIAC retrieval data is much more relevant than 10km MODIS data to characterize PM10 in this region of Italy which has a pretty limited geographical domain, but a broad variety of land usages and consequent particulate concentrations.
NASA Astrophysics Data System (ADS)
Green, S. J.; Tamburello, N.; Miller, S. E.; Akins, J. L.; Côté, I. M.
2013-06-01
A standard approach to improving the accuracy of reef fish population estimates derived from underwater visual censuses (UVCs) is the application of species-specific correction factors, which assumes that a species' detectability is constant under all conditions. To test this assumption, we quantified detection rates for invasive Indo-Pacific lionfish ( Pterois volitans and P. miles), which are now a primary threat to coral reef conservation throughout the Caribbean. Estimates of lionfish population density and distribution, which are essential for managing the invasion, are currently obtained through standard UVCs. Using two conventional UVC methods, the belt transect and stationary visual census (SVC), we assessed how lionfish detection rates vary with lionfish body size and habitat complexity (measured as rugosity) on invaded continuous and patch reefs off Cape Eleuthera, the Bahamas. Belt transect and SVC surveys performed equally poorly, with both methods failing to detect the presence of lionfish in >50 % of surveys where thorough, lionfish-focussed searches yielded one or more individuals. Conventional methods underestimated lionfish biomass by ~200 %. Crucially, detection rate varied significantly with both lionfish size and reef rugosity, indicating that the application of a single correction factor across habitats and stages of invasion is unlikely to accurately characterize local populations. Applying variable correction factors that account for site-specific lionfish size and rugosity to conventional survey data increased estimates of lionfish biomass, but these remained significantly lower than actual biomass. To increase the accuracy and reliability of estimates of lionfish density and distribution, monitoring programs should use detailed area searches rather than standard visual survey methods. Our study highlights the importance of accounting for sources of spatial and temporal variation in detection to increase the accuracy of survey data from coral reef systems.
Quantifying export production in the Southern Ocean: Implications for the Baxs proxy
NASA Astrophysics Data System (ADS)
Hernandez-Sanchez, Maria T.; Mills, Rachel A.; Planquette, HéLèNe; Pancost, Richard D.; Hepburn, Laura; Salter, Ian; Fitzgeorge-Balfour, Tania
2011-12-01
The water column and sedimentary Baxs distribution around the Crozet Plateau is used to decipher the controls and timing of barite formation and to evaluate how export production signals are recorded in sediments underlying a region of natural Fe fertilization within the Fe limited Southern Ocean. Export production estimated from preserved, vertical sedimentary Baxs accumulation rates are compared with published export fluxes assessed from an integrated study of the biological carbon pump to determine the validity of Baxs as a quantitative proxy under different Fe supply conditions typical of the Southern Ocean. Detailed assessment of the geochemical partitioning of Ba in sediments and the lithogenic end-member allows appropriate correction of the bulk Ba content and determination of the Baxs content of sediments and suspended particles. The upper water column distribution of Baxs is extremely heterogeneous spatially and temporally. Organic carbon/Baxs ratios in deep traps from the Fe fertilized region are similar to other oceanic settings allowing quantification of the inferred carbon export based on established algorithms. There appears to be some decoupling of POC and Ba export in the Fe limited region south of the Plateau. The export production across the Crozet Plateau inferred from the Baxs sedimentary proxy indicates that the Fe fertilized area to the north of the Plateau experiences enhanced export relative to equivalent Southern Ocean settings throughout the Holocene and that this influence may also have impacted the site to the south for significant periods. This interpretation is corroborated by alternative productivity proxies (opal accumulation, 231Paxs/230Thxs). Baxs can be used to quantify export production in complex settings such as naturally Fe-fertilized (volcanoclastic) areas, providing appropriate lithogenic correction is undertaken, and sediment focusing is corrected for along with evaluation of barite preservation.
NASA Astrophysics Data System (ADS)
José Polo, María; José Pérez-Palazón, María; Saénz de Rodrigáñez, Marta; Pimentel, Rafael; Arheimer, Berit
2017-04-01
Global hydrological models provide scientists and technicians with distributed data over medium to large areas from which assessment of water resource planning and use can be easily performed. However, scale conflicts between global models' spatial resolution and the local significant spatial scales in heterogeneous areas usually pose a constraint for the direct use and application of these models' results. The SWICCA (Service for Water Indicators in Climate Change Adaptation) Platform developed under the Copernicus Climate Change Service (C3S) offers a wide range of both climate and hydrological indicators obtained on a global scale with different time and spatial resolutions. Among the different study cases supporting the SWICCA demonstration of local impact assessment, the Sierra Nevada study case (South Spain) is a representative example of mountainous coastal catchments in the Mediterranean region. This work shows the lessons learnt during the study case development to derive local impact indicator tailored to suit the local end-users of water resource in this snow-dominated area. Different approaches were followed to select the most accurate method to downscale the global data and variables to the local level in a highly abrupt topography, in a sequential step approach. 1) SWICCA global climate variable downscaling followed by river flow simulation from a local hydrological model in selected control points in the catchment, together with 2) SWICCA global river flow values downscaling to the control points followed by corrections with local transfer functions were both tested against the available local river flow series of observations during the reference period. This test was performed for the different models and the available spatial resolutions included in the SWICCA platform. From the results, the second option, that is, the use of SWICCA river flow variables, performed the best approximations, once the local transfer functions were applied to the global values and an additional correction was performed based on the relative anomalies obtained instead of the absolute values. This approach was used to derive the future projections of selected local indicators for each end-user in the area under different climate change scenarios. Despite the spatial scale conflicts, the SWICCA river flow indicators (simulated by the E-HYPEv3.1.2 model) succeeded in approximating the observations during the reference period 1970-2000 when provided on a catchment scale, once local transfer functions and further anomaly correction were performed. Satisfactory results were obtained on a monthly scale for river flow in the main stream of the watershed, and on a daily scale for the headwater streams. The accessibility to the hydrological model WiMMed, which includes a snow module, locally validated in the study area has been crucial to downscale the SWICCA results and prove their usefulness.
Mu, Guangyu; Liu, Ying; Wang, Limin
2015-01-01
The spatial pooling method such as spatial pyramid matching (SPM) is very crucial in the bag of features model used in image classification. SPM partitions the image into a set of regular grids and assumes that the spatial layout of all visual words obey the uniform distribution over these regular grids. However, in practice, we consider that different visual words should obey different spatial layout distributions. To improve SPM, we develop a novel spatial pooling method, namely spatial distribution pooling (SDP). The proposed SDP method uses an extension model of Gauss mixture model to estimate the spatial layout distributions of the visual vocabulary. For each visual word type, SDP can generate a set of flexible grids rather than the regular grids from the traditional SPM. Furthermore, we can compute the grid weights for visual word tokens according to their spatial coordinates. The experimental results demonstrate that SDP outperforms the traditional spatial pooling methods, and is competitive with the state-of-the-art classification accuracy on several challenging image datasets.
Gong, Rui; Yang, Bi; Liu, Longqian; Dai, Yun; Zhang, Yudong; Zhao, Haoxin
2016-06-01
We conducted this study to explore the influence of the ocular residual aberrations changes on contrast sensitivity(CS)function in eyes undergoing orthokeratology using adaptive optics technique.Nineteen subjects’ nineteen eyes were included in this study.The subjects were between 12 and 20years(14.27±2.23years)of age.An adaptive optics(AO)system was adopted to measure and compensate the residual aberrations through a 4-mm artificial pupil,and at the same time the contrast sensitivities were measured at five spatial frequencies(2,4,8,16,and 32 cycles per degree).The CS measurements with and without AO correction were completed.The sequence of the measurements with and without AO correction was randomly arranged without informing the observers.A two-interval forced-choice procedure was used for the CS measurements.The paired t-test was used to compare the contrast sensitivity with and without AO correction at each spatial frequency.The results revealed that the AO system decreased the mean total root mean square(RMS)from 0.356μm to 0.160μm(t=10.517,P<0.001),and the mean total higher-order RMS from 0.246μm to 0.095μm(t=10.113,P<0.001).The difference in log contrast sensitivity with and without AO correction was significant only at 8cpd(t=-2.51,P=0.02).Thereby we concluded that correcting the ocular residual aberrations using adaptive optics technique could improve the contrast sensitivity function at intermediate spatial frequency in patients undergoing orthokeratology.
An approach for modelling snowcover ablation and snowmelt runoff in cold region environments
NASA Astrophysics Data System (ADS)
Dornes, Pablo Fernando
Reliable hydrological model simulations are the result of numerous complex interactions among hydrological inputs, landscape properties, and initial conditions. Determination of the effects of these factors is one of the main challenges in hydrological modelling. This situation becomes even more difficult in cold regions due to the ungauged nature of subarctic and arctic environments. This research work is an attempt to apply a new approach for modelling snowcover ablation and snowmelt runoff in complex subarctic environments with limited data while retaining integrity in the process representations. The modelling strategy is based on the incorporation of both detailed process understanding and inputs along with information gained from observations of basin-wide streamflow phenomenon; essentially a combination of deductive and inductive approaches. The study was conducted in the Wolf Creek Research Basin, Yukon Territory, using three models, a small-scale physically based hydrological model, a land surface scheme, and a land surface hydrological model. The spatial representation was based on previous research studies and observations, and was accomplished by incorporating landscape units, defined according to topography and vegetation, as the spatial model elements. Comparisons between distributed and aggregated modelling approaches showed that simulations incorporating distributed initial snowcover and corrected solar radiation were able to properly simulate snowcover ablation and snowmelt runoff whereas the aggregated modelling approaches were unable to represent the differential snowmelt rates and complex snowmelt runoff dynamics. Similarly, the inclusion of spatially distributed information in a land surface scheme clearly improved simulations of snowcover ablation. Application of the same modelling approach at a larger scale using the same landscape based parameterisation showed satisfactory results in simulating snowcover ablation and snowmelt runoff with minimal calibration. Verification of this approach in an arctic basin illustrated that landscape based parameters are a feasible regionalisation framework for distributed and physically based models. In summary, the proposed modelling philosophy, based on the combination of an inductive and deductive reasoning, is a suitable strategy for reliable predictions of snowcover ablation and snowmelt runoff in cold regions and complex environments.
Spatial coding-based approach for partitioning big spatial data in Hadoop
NASA Astrophysics Data System (ADS)
Yao, Xiaochuang; Mokbel, Mohamed F.; Alarabi, Louai; Eldawy, Ahmed; Yang, Jianyu; Yun, Wenju; Li, Lin; Ye, Sijing; Zhu, Dehai
2017-09-01
Spatial data partitioning (SDP) plays a powerful role in distributed storage and parallel computing for spatial data. However, due to skew distribution of spatial data and varying volume of spatial vector objects, it leads to a significant challenge to ensure both optimal performance of spatial operation and data balance in the cluster. To tackle this problem, we proposed a spatial coding-based approach for partitioning big spatial data in Hadoop. This approach, firstly, compressed the whole big spatial data based on spatial coding matrix to create a sensing information set (SIS), including spatial code, size, count and other information. SIS was then employed to build spatial partitioning matrix, which was used to spilt all spatial objects into different partitions in the cluster finally. Based on our approach, the neighbouring spatial objects can be partitioned into the same block. At the same time, it also can minimize the data skew in Hadoop distributed file system (HDFS). The presented approach with a case study in this paper is compared against random sampling based partitioning, with three measurement standards, namely, the spatial index quality, data skew in HDFS, and range query performance. The experimental results show that our method based on spatial coding technique can improve the query performance of big spatial data, as well as the data balance in HDFS. We implemented and deployed this approach in Hadoop, and it is also able to support efficiently any other distributed big spatial data systems.
Contrasting patterns of fine-scale herb layer species composition in temperate forests
NASA Astrophysics Data System (ADS)
Chudomelová, Markéta; Zelený, David; Li, Ching-Feng
2017-04-01
Although being well described at the landscape level, patterns in species composition of forest herb layer are rarely studied at smaller scales. Here, we examined fine-scale environmental determinants and spatial structures of herb layer communities in thermophilous oak- and hornbeam dominated forests of the south-eastern part of the Czech Republic. Species composition of herb layer vegetation and environmental variables were recorded within a fixed grid of 2 × 2 m subplots regularly distributed within 1-ha quadrate plots in three forest stands. For each site, environmental models best explaining species composition were constructed using constrained ordination analysis. Spatial eigenvector mapping was used to model and account for spatial structures in community variation. Mean Ellenberg indicator values calculated for each subplot were used for ecological interpretation of spatially structured residual variation. The amount of variation explained by environmental and spatial models as well as the selection of variables with the best explanatory power differed among sites. As an important environmental factor, relative elevation was common to all three sites, while pH and canopy openness were shared by two sites. Both environmental and community variation was mostly coarse-scaled, as was the spatially structured portion of residual variation. When corrected for bias due to spatial autocorrelation, those environmental factors with already weak explanatory power lost their significance. Only a weak evidence of possibly omitted environmental predictor was found for autocorrelated residuals of site models using mean Ellenberg indicator values. Community structure was determined by different factors at different sites. The relative importance of environmental filtering vs. spatial processes was also site specific, implying that results of fine-scale studies tend to be shaped by local conditions. Contrary to expectations based on other studies, overall dominance of spatial processes at fine scale has not been detected. Ecologists should keep this in mind when making generalizations about community dynamics.
NASA Astrophysics Data System (ADS)
Nambu, Ryogen; Saito, Hajime; Tanaka, Yoshio; Higano, Junya; Kuwahara, Hisami
2012-03-01
There are many studies on spatial distributions of Asari clam Ruditapes philippinarum adults on tidal flats but few have dealt with spatial distributions of newly settled Asari clam (<0.3 mm shell length, indicative of settlement patterns) in relation to physical/topographical conditions on tidal flats. We examined small-scale spatial distributions of newly settled individuals on the Matsunase tidal flat, central Japan, during the low spring tides on two days 29th-30th June 2007, together with the shear stress from waves and currents on the flat. The characteristics of spatial distribution of newly settled Asari clam markedly varied depending on both of hydrodynamic and topographical conditions on the tidal flat. Using generalized linear models (GLMs), factors responsible for affecting newly settled Asari clam density and its spatial distribution were distinguished between sampling days, with "crest" sites always having a negative influence each on the density and the distribution on both sampling days. The continuously recorded data for the wave-current flows at the "crest" site on the tidal flat showed that newly settled Asari clam, as well as bottom sediment particles, at the "crest" site to be easily displaced. Small-scale spatial distributions of newly settled Asari clam changed with more advanced benthic stages in relation to the wave shear stress.
NASA Astrophysics Data System (ADS)
Kwon, Jihun; Sutherland, Kenneth; Hashimoto, Takayuki; Shirato, Hiroki; Date, Hiroyuki
2016-10-01
Gold nanoparticles (GNPs) have been recognized as a promising candidate for a radiation sensitizer. A proton beam incident on a GNP can produce secondary electrons, resulting in an enhancement of the dose around the GNP. However, little is known about the spatial distribution of dose enhancement around the GNP, especially in the direction along the incident proton. The purpose of this study is to determine the spatial distribution of dose enhancement by taking the incident direction into account. Two steps of calculation were conducted using the Geant4 Monte Carlo simulation toolkit. First, the energy spectra of 100 and 195 MeV protons colliding with a GNP were calculated at the Bragg peak and three other depths around the peak in liquid water. Second, the GNP was bombarded by protons with the obtained energy spectra. Radial dose distributions were computed along the incident beam direction. The spatial distributions of the dose enhancement factor (DEF) and subtracted dose (Dsub) were then evaluated. The spatial DEF distributions showed hot spots in the distal radial region from the proton beam axis. The spatial Dsub distribution isotropically spread out around the GNP. Low energy protons caused higher and wider dose enhancement. The macroscopic dose enhancement in clinical applications was also evaluated. The results suggest that the consideration of the spatial distribution of GNPs in treatment planning will maximize the potential of GNPs.
Spatial Distribution of Surface Soil Moisture in a Small Forested Catchment
Predicting the spatial distribution of soil moisture is an important hydrological question. We measured the spatial distribution of surface soil moisture (upper 6 cm) using an Amplitude Domain Reflectometry sensor at the plot scale (2 × 2 m) and small catchment scale (0.84 ha) in...
Chen, Lyu Feng; Zhu, Guo Ping
2018-03-01
Based on Antarctic krill fishery and marine environmental data collected by scientific observers, using geographically weighted regression (GWR) model, we analyzed the effects of the factors with spatial attributes, i.e., depth of krill swarm (DKS) and distance from fishing position to shore (DTS), and sea surface temperature (SST), on the spatial distribution of fishing ground in the northern South Shetland Islands. The results showed that there was no significant aggregation in spatial distribution of catch per unit fishing effort (CPUE). Spatial autocorrelations (positive) among three factors were observed in 2010 and 2013, but were not in 2012 and 2016. Results from GWR model showed that the extent for the impacts on spatial distribution of CPUEs varied among those three factors, following the order DKS>SST>DTS. Compared to the DKS and DTS, the impact of SST on the spatial distribution of CPUEs presented adverse trend in the eastern and western parts of the South Shetland Islands. Negative correlations occurred for the spatial effects of DKS and DTS on distribution of CPUEs, though with inter-annual and regional variation. Our results provide metho-dological reference for researches on the underlying mechanism for fishing ground formation for Antarctic krill fishery.
Muška, Milan; Tušer, Michal; Frouzová, Jaroslava; Mrkvička, Tomáš; Ricard, Daniel; Seďa, Jaromír; Morelli, Federico; Kubečka, Jan
2018-03-29
Understanding spatial distribution of organisms in heterogeneous environment remains one of the chief issues in ecology. Spatial organization of freshwater fish was investigated predominantly on large-scale, neglecting important local conditions and ecological processes. However, small-scale processes are of an essential importance for individual habitat preferences and hence structuring trophic cascades and species coexistence. In this work, we analysed the real-time spatial distribution of pelagic freshwater fish in the Římov Reservoir (Czechia) observed by hydroacoustics in relation to important environmental predictors during 48 hours at 3-h interval. Effect of diurnal cycle was revealed of highest significance in all spatial models with inverse trends between fish distribution and predictors in day and night in general. Our findings highlighted daytime pelagic fish distribution as highly aggregated, with general fish preferences for central, deep and highly illuminated areas, whereas nighttime distribution was more disperse and fish preferred nearshore steep sloped areas with higher depth. This turnover suggests prominent movements of significant part of fish assemblage between pelagic and nearshore areas on a diel basis. In conclusion, hydroacoustics, GIS and spatial modelling proved as valuable tool for predicting local fish distribution and elucidate its drivers, which has far reaching implications for understanding freshwater ecosystem functioning.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Hammond, Glenn Edward; Song, Xuehang; Ye, Ming
A new approach is developed to delineate the spatial distribution of discrete facies (geological units that have unique distributions of hydraulic, physical, and/or chemical properties) conditioned not only on direct data (measurements directly related to facies properties, e.g., grain size distribution obtained from borehole samples) but also on indirect data (observations indirectly related to facies distribution, e.g., hydraulic head and tracer concentration). Our method integrates for the first time ensemble data assimilation with traditional transition probability-based geostatistics. The concept of level set is introduced to build shape parameterization that allows transformation between discrete facies indicators and continuous random variables. Themore » spatial structure of different facies is simulated by indicator models using conditioning points selected adaptively during the iterative process of data assimilation. To evaluate the new method, a two-dimensional semi-synthetic example is designed to estimate the spatial distribution and permeability of two distinct facies from transient head data induced by pumping tests. The example demonstrates that our new method adequately captures the spatial pattern of facies distribution by imposing spatial continuity through conditioning points. The new method also reproduces the overall response in hydraulic head field with better accuracy compared to data assimilation with no constraints on spatial continuity on facies.« less
Rojas, Kristians Diaz; Montero, Maria L.; Yao, Jorge; Messing, Edward; Fazili, Anees; Joseph, Jean; Ou, Yangming; Rubens, Deborah J.; Parker, Kevin J.; Davatzikos, Christos; Castaneda, Benjamin
2015-01-01
Abstract. A methodology to study the relationship between clinical variables [e.g., prostate specific antigen (PSA) or Gleason score] and cancer spatial distribution is described. Three-dimensional (3-D) models of 216 glands are reconstructed from digital images of whole mount histopathological slices. The models are deformed into one prostate model selected as an atlas using a combination of rigid, affine, and B-spline deformable registration techniques. Spatial cancer distribution is assessed by counting the number of tumor occurrences among all glands in a given position of the 3-D registered atlas. Finally, a difference between proportions is used to compare different spatial distributions. As a proof of concept, we compare spatial distributions from patients with PSA greater and less than 5 ng/ml and from patients older and younger than 60 years. Results suggest that prostate cancer has a significant difference in the right zone of the prostate between populations with PSA greater and less than 5 ng/ml. Age does not have any impact in the spatial distribution of the disease. The proposed methodology can help to comprehend prostate cancer by understanding its spatial distribution and how it changes according to clinical parameters. Finally, this methodology can be easily adapted to other organs and pathologies. PMID:26236756
NASA Astrophysics Data System (ADS)
Yang, He; Ma, Ben; Du, Qian; Yang, Chenghai
2010-08-01
In this paper, we propose approaches to improve the pixel-based support vector machine (SVM) classification for urban land use and land cover (LULC) mapping from airborne hyperspectral imagery with high spatial resolution. Class spatial neighborhood relationship is used to correct the misclassified class pairs, such as roof and trail, road and roof. These classes may be difficult to be separated because they may have similar spectral signatures and their spatial features are not distinct enough to help their discrimination. In addition, misclassification incurred from within-class trivial spectral variation can be corrected by using pixel connectivity information in a local window so that spectrally homogeneous regions can be well preserved. Our experimental results demonstrate the efficiency of the proposed approaches in classification accuracy improvement. The overall performance is competitive to the object-based SVM classification.
NASA Astrophysics Data System (ADS)
Beltran, Mario A.; Paganin, David M.; Pelliccia, Daniele
2018-05-01
A simple method of phase-and-amplitude extraction is derived that corrects for image blurring induced by partially spatially coherent incident illumination using only a single intensity image as input. The method is based on Fresnel diffraction theory for the case of high Fresnel number, merged with the space-frequency description formalism used to quantify partially coherent fields and assumes the object under study is composed of a single-material. A priori knowledge of the object’s complex refractive index and information obtained by characterizing the spatial coherence of the source is required. The algorithm was applied to propagation-based phase-contrast data measured with a laboratory-based micro-focus x-ray source. The blurring due to the finite spatial extent of the source is embedded within the algorithm as a simple correction term to the so-called Paganin algorithm and is also numerically stable in the presence of noise.
Spatio-temporal patterns of key exploited marine species in the Northwestern Mediterranean Sea.
Morfin, Marie; Fromentin, Jean-Marc; Jadaud, Angélique; Bez, Nicolas
2012-01-01
This study analyzes the temporal variability/stability of the spatial distributions of key exploited species in the Gulf of Lions (Northwestern Mediterranean Sea). To do so, we analyzed data from the MEDITS bottom-trawl scientific surveys from 1994 to 2010 at 66 fixed stations and selected 12 key exploited species. We proposed a geostatistical approach to handle zero-inflated and non-stationary distributions and to test for the temporal stability of the spatial structures. Empirical Orthogonal Functions and other descriptors were then applied to investigate the temporal persistence and the characteristics of the spatial patterns. The spatial structure of the distribution (i.e. the pattern of spatial autocorrelation) of the 12 key species studied remained highly stable over the time period sampled. The spatial distributions of all species obtained through kriging also appeared to be stable over time, while each species displayed a specific spatial distribution. Furthermore, adults were generally more densely concentrated than juveniles and occupied areas included in the distribution of juveniles. Despite the strong persistence of spatial distributions, we also observed that the area occupied by each species was correlated to its abundance: the more abundant the species, the larger the occupation area. Such a result tends to support MacCall's basin theory, according to which density-dependence responses would drive the expansion of those 12 key species in the Gulf of Lions. Further analyses showed that these species never saturated their habitats, suggesting that they are below their carrying capacity; an assumption in agreement with the overexploitation of several of these species. Finally, the stability of their spatial distributions over time and their potential ability to diffuse outside their main habitats give support to Marine Protected Areas as a potential pertinent management tool.
Brady, Samuel; Yoshizumi, Terry; Toncheva, Greta; Frush, Donald
2010-01-01
Purpose: The authors present a means to measure high-resolution, two-dimensional organ dose distributions in an anthropomorphic phantom of heterogeneous tissue composition using XRQA radiochromic film. Dose distributions are presented for the lungs, liver, and kidneys to demonstrate the organ volume dosimetry technique. XRQA film response accuracy was validated using thermoluminescent dosimeters (TLDs). Methods: XRQA film and TLDs were first exposed at the center of two CTDI head phantoms placed end-to-end, allowing for a simple cylindrical phantom of uniform scatter material for verification of film response accuracy and sensitivity in a computed tomography (CT) exposure geometry; the TLD and film dosimeters were exposed separately. In a similar manner, TLDs and films were placed between cross-sectional slabs of a 5 yr old anthropomorphic phantom’s thorax and abdomen regions. The anthropomorphic phantom was used to emulate real pediatric patient geometry and scatter conditions. The phantom consisted of five different tissue types manufactured to attenuate the x-ray beam within 1%–3% of normal tissues at CT beam energies. Software was written to individually calibrate TLD and film dosimeter responses for different tissue attenuation factors, to spatially register dosimeters, and to extract dose responses from film for TLD comparison. TLDs were compared to film regions of interest extracted at spatial locations corresponding to the TLD locations. Results: For the CTDI phantom exposure, the film and TLDs measured an average difference in dose response of 45% (SD±2%). Similar comparisons within the anthropomorphic phantom also indicated a consistent difference, tracking along the low and high dose regions, for the lung (28%) (SD±8%) and liver and kidneys (15%) (SD±4%). The difference between the measured film and TLD dose values was due to the lower response sensitivity of the film that arose when the film was oriented with its large surface area parallel to the main axis of the CT beam. The consistency in dose response difference allowed for a tissue specific correction to be applied. Once corrected, the average film response agreed to better than 3% (SD±2%) for the CTDI scans, and for the anthropomorphic phantom scans: 3% (SD±3%) for the lungs, 5% (SD±3%) for the liver, and 4% (SD±3%) for the kidneys. Additionally, XRQA film measured a heterogeneous dose distribution within the organ volumes. The extent of the dose distribution heterogeneity was not measurable with the TLDs due to the limitation on the number of TLDs loadable in the regions of the phantom organs. In this regard, XRQA film demonstrated an advantage over the TLD method by discovering a 15% greater maximum dose to lung in a region unmeasured by TLDs. Conclusions: The films demonstrated a lower sensitivity to absorbed dose measurements due to the geometric inefficiency of measuring dose from a beam situated end-on to the film. Once corrected, the film demonstrated equivalent dose measurement accuracy as TLD detectors with the added advantage of relatively simple measurement of high-resolution dose distributions throughout organ volumes. PMID:20964198
Development of Pseudorandom Binary Arrays for Calibration of Surface Profile Metrology Tools
DOE Office of Scientific and Technical Information (OSTI.GOV)
Barber, S.K.; Takacs, P.; Soldate, P.
2009-12-01
Optical metrology tools, especially for short wavelengths (extreme ultraviolet and x-ray), must cover a wide range of spatial frequencies from the very low, which affects figure, to the important mid-spatial frequencies and the high spatial frequency range, which produces undesirable scattering. A major difficulty in using surface profilometers arises due to the unknown point-spread function (PSF) of the instruments [G. D. Boreman, Modulation Transfer Function in Optical and Electro-Optical Systems (SPIE, Bellingham, WA, 2001)] that is responsible for distortion of the measured surface profile. Generally, the distortion due to the PSF is difficult to account for because the PSF ismore » a complex function that comes to the measurement via the convolution operation, while the measured profile is described with a real function. Accounting for instrumental PSF becomes significantly simpler if the result of measurement of a profile is presented in the spatial frequency domain as a power spectral density (PSD) distribution [J. W. Goodman, Introduction to Fourier Optics, 3rd ed. (Roberts and Company, Englewood, CO, 2005)]. For example, measured PSD distributions provide a closed set of data necessary for three-dimensional calculations of scattering of light by the optical surfaces [E. L. Church et al., Opt. Eng. (Bellingham) 18, 125 (1979); J. C. Stover, Optical Scattering, 2nd ed. (SPIE Optical Engineering Press, Bellingham, WA, 1995)]. The distortion of the surface PSD distribution due to the PSF can be modeled with the modulation transfer function (MTF), which is defined over the spatial frequency bandwidth of the instrument. The measured PSD distribution can be presented as a product of the squared MTF and the ideal PSD distribution inherent for the system under test. Therefore, the instrumental MTF can be evaluated by comparing a measured PSD distribution of a known test surface with the corresponding ideal numerically simulated PSD. The square root of the ratio of the measured and simulated PSD distributions gives the MTF of the instrument. The applicability of the MTF concept to phase map measurements with optical interferometric microscopes needs to be experimentally verified as the optical tool and algorithms may introduce nonlinear artifacts into the process. In previous work [V. V. Yashchuk et al., Proc. SPIE 6704, 670408 (2007); Valeriy V. Yashchuk et al., Opt. Eng. (Bellingham) 47, 073602 (2008)] the instrumental MTF of a surface profiler was precisely measured using reference test surfaces based on binary pseudorandom (BPR) gratings. Here, the authors present results of fabricating and using two-dimensional (2D) BPR arrays that allow for a direct 2D calibration of the instrumental MTF. BPR sequences are widely used in engineering and communication applications such as global position systems and wireless communication protocols. The ideal BPR pattern has a flat 'white noise' response over the entire range of spatial frequencies of interest. The BPR array used here is based on the uniformly redundant array (URA) prescription [E. E. Fenimore and T. M. Cannon, Appl. Opt. 17, 337 (1978)] initially used for x-ray and gamma ray astronomy applications. The URA's superior imaging capability originates from the fact that its cyclical autocorrelation function very closely approximates a delta function, which produces a flat PSD. Three different size BPR array patterns were fabricated by electron beam lithography and induction coupled plasma etching of silicon. The basic size units were 200, 400, and 600 nm. Two different etch processes were used, CF{sub 4}/Ar and HBr, which resulted in undercut and vertical sidewall profiles, respectively. The 2D BPR arrays were used as standard test surfaces for MTF calibration of the MicroMap{trademark}-570 interferometric microscope using all available objectives. The MicroMap{trademark}-570 interferometric microscope uses incoherent illumination from a tungsten filament source and common path modulated phase shifting interference to produce a set of interferograms detected on a change coupled device. Mathematical algorithms applied to the datasets yield the surface phase map. The HBr etched two-dimensional BPR arrays have proven to be a very effective calibration standard making possible direct calibration corrections without the need of additional calculation considerations, while departures from the ideal vertical sidewall require an additional correction term for the CF{sub 4}/Ar etched samples [Samuel K. Barber et al., Abstract to Optics and Photonics 2009: Optical Engineering and Applications Symposium, San Diego, CA, 2-6 August 2009]. Initial surface roughness of low cost 'prime' wafers limits low magnification calibration but should not be a limitation if better polished samples are used.« less
NASA Astrophysics Data System (ADS)
Hu, Haixin
This dissertation consists of two parts. The first part studies the sample selection and spatial models of housing price index using transaction data on detached single-family houses of two California metropolitan areas from 1990 through 2008. House prices are often spatially correlated due to shared amenities, or when the properties are viewed as close substitutes in a housing submarket. There have been many studies that address spatial correlation in the context of housing markets. However, none has used spatial models to construct housing price indexes at zip code level for the entire time period analyzed in this dissertation to the best of my knowledge. In this paper, I study a first-order autoregressive spatial model with four different weighing matrix schemes. Four sets of housing price indexes are constructed accordingly. Gatzlaff and Haurin (1997, 1998) study the sample selection problem in housing index by using Heckman's two-step method. This method, however, is generally inefficient and can cause multicollinearity problem. Also, it requires data on unsold houses in order to carry out the first-step probit regression. Maximum likelihood (ML) method can be used to estimate a truncated incidental model which allows one to correct for sample selection based on transaction data only. However, convergence problem is very prevalent in practice. In this paper I adopt Lewbel's (2007) sample selection correction method which does not require one to model or estimate the selection model, except for some very general assumptions. I then extend this method to correct for spatial correlation. In the second part, I analyze the U.S. gasoline market with a disequilibrium model that allows lagged-latent variables, endogenous prices, and panel data with fixed effects. Most existing studies (see the survey of Espey, 1998, Energy Economics) of the gasoline market assume equilibrium. In practice, however, prices do not always adjust fast enough to clear the market. Equilibrium assumptions greatly simplify statistical inference, but are very restrictive and can produce conflicting estimates. For example, econometric models of markets that assume equilibrium often produce more elastic demand price elasticity than their disequilibrium counterparts (Holt and Johnson, 1989, Review of Economics and Statistics, Oczkowski, 1998, Economics Letters). The few studies that allow disequilibrium, however, have been limited to macroeconomic time-series data without lagged-latent variables. While time series data allows one to investigate national trends, it cannot be used to identify and analyze regional differences and the role of local markets. Exclusion of the lagged-latent variables is also undesirable because such variables capture adjustment costs and inter-temporal spillovers. Simulation methods offer tractable solutions to dynamic and panel data disequilibrium models (Lee, 1997, Journal of Econometrics), but assume normally distributed errors. This paper compares estimates of price/income elasticity and excess supply/demand across time periods, regions, and model specifications, using both equilibrium and disequilibrium methods. In the equilibrium model, I compare the within group estimator with Anderson and Hsiao's first-difference 2SLS estimator. In the disequilibrium model, I extend Amemiya's 2SLS by using Newey's efficient estimator with optimal instruments.
NASA Technical Reports Server (NTRS)
Yasunari, Teppei J.; Colarco, Peter R.; Lau, William K. M.; Osada, Kazuo; Kido, Mizuka; Mahanama, Sarith P. P.; Kim, Kyu-Myong; Da Silva, Arlindo M.
2015-01-01
We compared the observed total dust deposition fluxes during precipitation (TDP) mainly at Toyama in Japan during the period January - April 2009 with results available from four NASA GEOS-5 global model experiments. The modeled results were obtained from three previous experiments and carried out in one experiment, which were all driven by assimilated meteorology and simulating aerosol distributions for the time period. We focus mainly on the observations of two distinct TDP events, which were reported in Osada et al. (2011), at Toyama, Japan, in February (Event B) and March 2009 (Event C). Although all of our GEOS-5 simulations captured aspects of the observed TDP, we found that our low horizontal spatial resolution control experiment performed generally the worst. The other three experiments were run at a higher spatial resolution, with the first differing only in that respect from the control, the second adding imposed a prescribed corrected precipitation product, and the final experiment adding as well assimilation of aerosol optical depth based on MODIS observations. During Event C, the increased horizontal resolution could increase TDP with precipitation increase. There was no significant improvement, however, due to the imposition of the corrected precipitation product. The simulation that incorporated aerosol data assimilation performed was by far the best for this event, but even so could only reproduce less than half of the observed TDP despite the significantly increased atmospheric dust mass concentrations. All three of the high spatial resolution experiments had higher simulated precipitation at Toyama than was observed and that in the lower resolution control run. During Event B, the aerosol data assimilation run did not perform appreciably better than the other higher resolution simulations, suggesting that upstream conditions (i.e., upstream cloudiness), or vertical or horizontal misplacement of the dust plume did not allow for significant improvement in the simulated aerosol distributions. Furthermore, a detailed comparison of observed hourly precipitation and surface particulate mass concentration data suggests that the observed TDP during Event B was highly dependent on short periods of weak precipitation correlated with elevated dust surface concentrations, important details possibly not captured well in a current global model.
Analytical-Based Partial Volume Recovery in Mouse Heart Imaging
NASA Astrophysics Data System (ADS)
Dumouchel, Tyler; deKemp, Robert A.
2011-02-01
Positron emission tomography (PET) is a powerful imaging modality that has the ability to yield quantitative images of tracer activity. Physical phenomena such as photon scatter, photon attenuation, random coincidences and spatial resolution limit quantification potential and must be corrected to preserve the accuracy of reconstructed images. This study focuses on correcting the partial volume effects that arise in mouse heart imaging when resolution is insufficient to resolve the true tracer distribution in the myocardium. The correction algorithm is based on fitting 1D profiles through the myocardium in gated PET images to derive myocardial contours along with blood, background and myocardial activity. This information is interpolated onto a 2D grid and convolved with the tomograph's point spread function to derive regional recovery coefficients enabling partial volume correction. The point spread function was measured by placing a line source inside a small animal PET scanner. PET simulations were created based on noise properties measured from a reconstructed PET image and on the digital MOBY phantom. The algorithm can estimate the myocardial activity to within 5% of the truth when different wall thicknesses, backgrounds and noise properties are encountered that are typical of healthy FDG mouse scans. The method also significantly improves partial volume recovery in simulated infarcted tissue. The algorithm offers a practical solution to the partial volume problem without the need for co-registered anatomic images and offers a basis for improved quantitative 3D heart imaging.
2014-01-01
Background National data on body mass index (BMI), computed from self-reported height and weight, is readily available for many populations including the Canadian population. Because self-reported weight is found to be systematically under-reported, it has been proposed that the bias in self-reported BMI can be corrected using equations derived from data sets which include both self-reported and measured height and weight. Such correction equations have been developed and adopted. We aim to evaluate the usefulness (i.e., distributional similarity; sensitivity and specificity; and predictive utility vis-à-vis disease outcomes) of existing and new correction equations in population-based research. Methods The Canadian Community Health Surveys from 2005 and 2008 include both measured and self-reported values of height and weight, which allows for construction and evaluation of correction equations. We focused on adults age 18–65, and compared three correction equations (two correcting weight only, and one correcting BMI) against self-reported and measured BMI. We first compared population distributions of BMI. Second, we compared the sensitivity and specificity of self-reported BMI and corrected BMI against measured BMI. Third, we compared the self-reported and corrected BMI in terms of association with health outcomes using logistic regression. Results All corrections outperformed self-report when estimating the full BMI distribution; the weight-only correction outperformed the BMI-only correction for females in the 23–28 kg/m2 BMI range. In terms of sensitivity/specificity, when estimating obesity prevalence, corrected values of BMI (from any equation) were superior to self-report. In terms of modelling BMI-disease outcome associations, findings were mixed, with no correction proving consistently superior to self-report. Conclusions If researchers are interested in modelling the full population distribution of BMI, or estimating the prevalence of obesity in a population, then a correction of any kind included in this study is recommended. If the researcher is interested in using BMI as a predictor variable for modelling disease, then both self-reported and corrected BMI result in biased estimates of association. PMID:24885210
Han, Buhm; Kang, Hyun Min; Eskin, Eleazar
2009-01-01
With the development of high-throughput sequencing and genotyping technologies, the number of markers collected in genetic association studies is growing rapidly, increasing the importance of methods for correcting for multiple hypothesis testing. The permutation test is widely considered the gold standard for accurate multiple testing correction, but it is often computationally impractical for these large datasets. Recently, several studies proposed efficient alternative approaches to the permutation test based on the multivariate normal distribution (MVN). However, they cannot accurately correct for multiple testing in genome-wide association studies for two reasons. First, these methods require partitioning of the genome into many disjoint blocks and ignore all correlations between markers from different blocks. Second, the true null distribution of the test statistic often fails to follow the asymptotic distribution at the tails of the distribution. We propose an accurate and efficient method for multiple testing correction in genome-wide association studies—SLIDE. Our method accounts for all correlation within a sliding window and corrects for the departure of the true null distribution of the statistic from the asymptotic distribution. In simulations using the Wellcome Trust Case Control Consortium data, the error rate of SLIDE's corrected p-values is more than 20 times smaller than the error rate of the previous MVN-based methods' corrected p-values, while SLIDE is orders of magnitude faster than the permutation test and other competing methods. We also extend the MVN framework to the problem of estimating the statistical power of an association study with correlated markers and propose an efficient and accurate power estimation method SLIP. SLIP and SLIDE are available at http://slide.cs.ucla.edu. PMID:19381255
NASA Astrophysics Data System (ADS)
Wang, Zhao; Yang, Shan; Wang, Shuguang; Shen, Yan
2017-10-01
The assessment of the dynamic urban structure has been affected by lack of timely and accurate spatial information for a long period, which has hindered the measurements of structural continuity at the macroscale. Defense meteorological satellite program's operational linescan system (DMSP/OLS) nighttime light (NTL) data provide an ideal source for urban information detection with a long-time span, short-time interval, and wide coverage. In this study, we extracted the physical boundaries of urban clusters from corrected NTL images and quantitatively analyzed the structure of the urban cluster system based on rank-size distribution, spatial metrics, and Mann-Kendall trend test. Two levels of urban cluster systems in the Yangtze River Delta region (YRDR) were examined. We found that (1) in the entire YRDR, the urban cluster system showed a periodic process, with a significant trend of even distribution before 2007 but an unequal growth pattern after 2007, and (2) at the metropolitan level, vast disparities exist in four metropolitan areas for the fluctuations of Pareto's exponent, the speed of cluster expansion, and the dominance of core cluster. The results suggest that the extracted urban cluster information from NTL data effectively reflect the evolving nature of regional urbanization, which in turn can aid in the planning of cities and help achieve more sustainable regional development.
Chebli, Youssef; Kaneda, Minako; Zerzour, Rabah; Geitmann, Anja
2012-01-01
The pollen tube is a cellular protuberance formed by the pollen grain, or male gametophyte, in flowering plants. Its principal metabolic activity is the synthesis and assembly of cell wall material, which must be precisely coordinated to sustain the characteristic rapid growth rate and to ensure geometrically correct and efficient cellular morphogenesis. Unlike other model species, the cell wall of the Arabidopsis (Arabidopsis thaliana) pollen tube has not been described in detail. We used immunohistochemistry and quantitative image analysis to provide a detailed profile of the spatial distribution of the major cell wall polymers composing the Arabidopsis pollen tube cell wall. Comparison with predictions made by a mechanical model for pollen tube growth revealed the importance of pectin deesterification in determining the cell diameter. Scanning electron microscopy demonstrated that cellulose microfibrils are oriented in near longitudinal orientation in the Arabidopsis pollen tube cell wall, consistent with a linear arrangement of cellulose synthase CESA6 in the plasma membrane. The cellulose label was also found inside cytoplasmic vesicles and might originate from an early activation of cellulose synthases prior to their insertion into the plasma membrane or from recycling of short cellulose polymers by endocytosis. A series of strategic enzymatic treatments also suggests that pectins, cellulose, and callose are highly cross linked to each other. PMID:23037507
NASA Astrophysics Data System (ADS)
Dryzek, Jerzy; Siemek, Krzysztof
2013-08-01
The spatial distribution of positrons emitted from radioactive isotopes into stacks or layered samples is a subject of the presented report. It was found that Monte Carlo (MC) simulations using GEANT4 code are not able to describe correctly the experimental data of the positron fractions in stacks. The mathematical model was proposed for calculations of the implantation profile or positron fractions in separated layers or foils being components of a stack. The model takes into account only two processes, i.e., the positron absorption and backscattering at interfaces. The mathematical formulas were applied in the computer program called LYS-1 (layers profile analysis). The theoretical predictions of the model were in the good agreement with the results of the MC simulations for the semi infinite sample. The experimental verifications of the model were performed on the symmetrical and non-symmetrical stacks of different foils. The good agreement between the experimental and calculated fractions of positrons in components of a stack was achieved. Also the experimental implantation profile obtained using the depth scanning of positron implantation technique is very well described by the theoretical profile obtained within the proposed model. The LYS-1 program allows us also to calculate the fraction of positrons which annihilate in the source, which can be useful in the positron spectroscopy.
Yunqi Wang; Najafizadeh, Laleh
2016-08-01
One of the main challenges in EEG-based biometric systems is to extract reliable signatures of individuality from recorded EEG data that are also invariant against time. In this paper, we investigate the invariability of features that are extracted based on the spatial distribution of the spectral power of EEG data corresponding to 2-second eyes-closed resting-state (ECRS) recording, in different scenarios. Eyes-closed resting-state EEG signals in 4 healthy adults are recorded in two different sessions with an interval of at least one week between sessions. The performance in terms of correct recognition rate (CRR) is examined when the training and testing datasets are chosen from the same recording session, and when the training and testing datasets are chosen from different sessions. It is shown that an CRR of 92% can be achieved based on the proposed features when the training and testing datasets are taken from different sessions. To reduce the number of recording channels, principal component analysis (PCA) is also employed to identify channels that carry the most discriminatory information across individuals. High CRR is obtained based on the data from channels mostly covering the occipital region. The results suggest that features based on the spatial distribution of the spectral power of the short-time (e.g. 2 seconds) ECRS recordings can have great potentials in EEG-based biometric identification systems.
Aerosol radiative forcing from GEO satellite data over land surfaces
NASA Astrophysics Data System (ADS)
Costa, Maria J.; Silva, Ana M.
2005-10-01
Aerosols direct and indirect effects on the Earth's climate are widely recognized but have yet to be adequately quantified. Difficulties arise due to the very high spatial and temporal variability of aerosols, which is a major cause of uncertainties in radiative forcing studies. The effective monitoring of the global aerosol distribution is only made possible by satellite monitoring and this is the reason why the interest in aerosol observations from satellite passive radiometers is steadily increasing. From the point of view of the study of land surfaces, the atmosphere with its constituents represents an obscurant whose effects should be as much as possible eliminated, being this process sometimes referred to as atmospheric correction. In absence of clouds and using spectral intervals where gas absorption can be avoided to a great extent, only the aerosol effect remains to be corrected. The monitoring of the aerosol particles present in the atmosphere is then crucial to succeed in doing an accurate atmospheric correction, otherwise the surface properties may be inadequately characterised. However, the atmospheric correction over land surfaces turns out to be a difficult task since surface reflection competes with the atmospheric component of the signal. On the other hand, a single mean pre-established aerosol characterisation would not be sufficient for this purpose due to very high spatial and temporal variability of aerosols and their unpredictability, especially what concerns particulary intense "events" such as biomass burning and forest fires, desert dust episodes and volcanic eruptions. In this context, an operational methodology has been developed at the University of Evora - Evora Geophysics Centre (CGE), in the framework of the Satellite Application Facility for Land Surface Analysis - Land SAF, to derive an Aerosol Product from the Spinning Enhanced Visible and Infrared Imager (SEVIRI) data, flying on the Geostationary (GEO) satellite system Meteosat-8. The aerosol characterization obtained is used to calculate the fluxes and estimate the aerosol radiative forcing at the top of the atmosphere. The methodology along with the results of the aerosol properties and radiative forcing using SEVIRI images is presented. The aerosol optical thickness results are compared with ground-based measurements from the Aerosol Robotic NETwork (AERONET), to assess the accuracy of the methodology presented.
NASA Astrophysics Data System (ADS)
Ahn, J. B.; Hur, J.
2015-12-01
The seasonal prediction of both the surface air temperature and the first-flowering date (FFD) over South Korea are produced using dynamical downscaling (Hur and Ahn, 2015). Dynamical downscaling is performed using Weather Research and Forecast (WRF) v3.0 with the lateral forcing from hourly outputs of Pusan National University (PNU) coupled general circulation model (CGCM) v1.1. Gridded surface air temperature data with high spatial (3km) and temporal (daily) resolution are obtained using the physically-based dynamical models. To reduce systematic bias, simple statistical correction method is then applied to the model output. The FFDs of cherry, peach and pear in South Korea are predicted for the decade of 1999-2008 by applying the corrected daily temperature predictions to the phenological thermal-time model. The WRF v3.0 results reflect the detailed topographical effect, despite having cold and warm biases for warm and cold seasons, respectively. After applying the correction, the mean temperature for early spring (February to April) well represents the general pattern of observation, while preserving the advantages of dynamical downscaling. The FFD predictabilities for the three species of trees are evaluated in terms of qualitative, quantitative and categorical estimations. Although FFDs derived from the corrected WRF results well predict the spatial distribution and the variation of observation, the prediction performance has no statistical significance or appropriate predictability. The approach used in the study may be helpful in obtaining detailed and useful information about FFD and regional temperature by accounting for physically-based atmospheric dynamics, although the seasonal predictability of flowering phenology is not high enough. Acknowledgements This work was carried out with the support of the Rural Development Administration Cooperative Research Program for Agriculture Science and Technology Development under Grant Project No. PJ009953 and Project No. PJ009353, Republic of Korea. Reference Hur, J., J.-B. Ahn, 2015. Seasonal Prediction of Regional Surface Air Temperature and First-flowering Date over South Korea, Int. J. Climatol., DOI: 10.1002/joc.4323.
Cosmological Distance Scale to Gamma-Ray Bursts
NASA Astrophysics Data System (ADS)
Azzam, W. J.; Linder, E. V.; Petrosian, V.
1993-05-01
The source counts or the so-called log N -- log S relations are the primary data that constrain the spatial distribution of sources with unknown distances, such as gamma-ray bursts. In order to test galactic, halo, and cosmological models for gamma-ray bursts we compare theoretical characteristics of the log N -- log S relations to those obtained from data gathered by the BATSE instrument on board the Compton Observatory (GRO) and other instruments. We use a new and statistically correct method, that takes proper account of the variable nature of the triggering threshold, to analyze the data. Constraints on models obtained by this comparison will be presented. This work is supported by NASA grants NAGW 2290, NAG5 2036, and NAG5 1578.
A SiPM based real time dosimeter for radiotherapic beams
NASA Astrophysics Data System (ADS)
Berra, A.; Conti, V.; Lietti, D.; Milan, L.; Novati, C.; Ostinelli, A.; Prest, M.; Romanó, C.; Vallazza, E.
2015-02-01
This paper describes the development of a scintillator dosimeter prototype for radiotherapic applications based on plastic scintillating fibers readout by Silicon PhotoMultipliers. The dosimeter, whose probes are water equivalent, could be used for quality control measurements, beam characterization and in vivo dosimetry, allowing a real time measurement of the dose spatial distribution. This paper describes the preliminary percentual depth dose scan performed with clinical 6 and 18 MV photon beams, comparing the results with a reference curve. The measurements were performed using a Varian Clinac iX linear accelerator at the Radiotherapy Department of the St. Anna Hospital in Como (IT). The prototype has given promising results, allowing real time measurements of relative dose without applying any correction factors.
Study on imaging spectrometer with smile and keystone eliminated
NASA Astrophysics Data System (ADS)
Zhang, Xiaolong; Yu, Kun; Zhang, Jun
2017-03-01
The formulas of image height in two-dimensional field about Gaussian and tilted imaging system of grating-based imaging spectrometer instrument (GISI) are deduced firstly, and the determined expressions of smile and keystone of GISI are obtained. It is proposed to correct the smile with off-axis lens, and the elimination effect of the smile is studied by means of spatial ray tracing. By controlling the degree of off-axis and the distribution of focal power of the off-axis lens, the long-wave infrared imaging spectrometer with well-eliminated smile and keystone is designed. The maximum of smile and keystone at working wavelengths in all fields of view are less than 8.57 μm and 13.33 μm, respectively.
Federal Register 2010, 2011, 2012, 2013, 2014
2010-02-02
... Management Program for Gas Distribution Pipelines; Correction AGENCY: Pipeline and Hazardous Materials Safety... DEPARTMENT OF TRANSPORTATION Pipeline and Hazardous Materials Safety Administration 49 CFR Part... Regulations to require operators of gas distribution pipelines to develop and implement integrity management...
Spatial and temporal distribution of trunk-injected imidacloprid in apple tree canopies.
Aćimović, Srđan G; VanWoerkom, Anthony H; Reeb, Pablo D; Vandervoort, Christine; Garavaglia, Thomas; Cregg, Bert M; Wise, John C
2014-11-01
Pesticide use in orchards creates drift-driven pesticide losses which contaminate the environment. Trunk injection of pesticides as a target-precise delivery system could greatly reduce pesticide losses. However, pesticide efficiency after trunk injection is associated with the underinvestigated spatial and temporal distribution of the pesticide within the tree crown. This study quantified the spatial and temporal distribution of trunk-injected imidacloprid within apple crowns after trunk injection using one, two, four or eight injection ports per tree. The spatial uniformity of imidacloprid distribution in apple crowns significantly increased with more injection ports. Four ports allowed uniform spatial distribution of imidacloprid in the crown. Uniform and non-uniform spatial distributions were established early and lasted throughout the experiment. The temporal distribution of imidacloprid was significantly non-uniform. Upper and lower crown positions did not significantly differ in compound concentration. Crown concentration patterns indicated that imidacloprid transport in the trunk occurred through radial diffusion and vertical uptake with a spiral pattern. By showing where and when a trunk-injected compound is distributed in the apple tree canopy, this study addresses a key knowledge gap in terms of explaining the efficiency of the compound in the crown. These findings allow the improvement of target-precise pesticide delivery for more sustainable tree-based agriculture. © 2014 Society of Chemical Industry.
2015-01-01
Background Multiscale approaches for integrating submodels of various levels of biological organization into a single model became the major tool of systems biology. In this paper, we have constructed and simulated a set of multiscale models of spatially distributed microbial communities and study an influence of unevenly distributed environmental factors on the genetic diversity and evolution of the community members. Results Haploid Evolutionary Constructor software http://evol-constructor.bionet.nsc.ru/ was expanded by adding the tool for the spatial modeling of a microbial community (1D, 2D and 3D versions). A set of the models of spatially distributed communities was built to demonstrate that the spatial distribution of cells affects both intensity of selection and evolution rate. Conclusion In spatially heterogeneous communities, the change in the direction of the environmental flow might be reflected in local irregular population dynamics, while the genetic structure of populations (frequencies of the alleles) remains stable. Furthermore, in spatially heterogeneous communities, the chemotaxis might dramatically affect the evolution of community members. PMID:25708911
NASA Astrophysics Data System (ADS)
Morin, Efrat; Marra, Francesco; Peleg, Nadav; Mei, Yiwen; Anagnostou, Emmanouil N.
2017-04-01
Rainfall frequency analysis is used to quantify the probability of occurrence of extreme rainfall and is traditionally based on rain gauge records. The limited spatial coverage of rain gauges is insufficient to sample the spatiotemporal variability of extreme rainfall and to provide the areal information required by management and design applications. Conversely, remote sensing instruments, even if quantitative uncertain, offer coverage and spatiotemporal detail that allow overcoming these issues. In recent years, remote sensing datasets began to be used for frequency analyses, taking advantage of increased record lengths and quantitative adjustments of the data. However, the studies so far made use of concepts and techniques developed for rain gauge (i.e. point or multiple-point) data and have been validated by comparison with gauge-derived analyses. These procedures add further sources of uncertainty and prevent from isolating between data and methodological uncertainties and from fully exploiting the available information. In this study, we step out of the gauge-centered concept presenting a direct comparison between at-site Intensity-Duration-Frequency (IDF) curves derived from different remote sensing datasets on corresponding spatial scales, temporal resolutions and records. We analyzed 16 years of homogeneously corrected and gauge-adjusted C-Band weather radar estimates, high-resolution CMORPH and gauge-adjusted high-resolution CMORPH over the Eastern Mediterranean. Results of this study include: (a) good spatial correlation between radar and satellite IDFs ( 0.7 for 2-5 years return period); (b) consistent correlation and dispersion in the raw and gauge adjusted CMORPH; (c) bias is almost uniform with return period for 12-24 h durations; (d) radar identifies thicker tail distributions than CMORPH and the tail of the distributions depends on the spatial and temporal scales. These results demonstrate the potential of remote sensing datasets for rainfall frequency analysis for management (e.g. warning and early-warning systems) and design (e.g. sewer design, large scale drainage planning)
Li, Tianxin; Zhou, Xing Chen; Ikhumhen, Harrison Odion; Difei, An
2018-05-01
In recent years, with the significant increase in urban development, it has become necessary to optimize the current air monitoring stations to reflect the quality of air in the environment. Highlighting the spatial representation of some air monitoring stations using Beijing's regional air monitoring station data from 2012 to 2014, the monthly mean particulate matter concentration (PM10) in the region was calculated and through the IDW interpolation method and spatial grid statistical method using GIS, the spatial distribution of PM10 concentration in the whole region was deduced. The spatial distribution variation of districts in Beijing using the gridding model was performed, and through the 3-year spatial analysis, PM10 concentration data including the variation and spatial overlay (1.5 km × 1.5 km cell resolution grid), the spatial distribution result obtained showed that the total PM10 concentration frequency variation exceeded the standard. It is very important to optimize the layout of the existing air monitoring stations by combining the concentration distribution of air pollutants with the spatial region using GIS.
Meng, Yuguang; Lei, Hao
2010-06-01
An efficient iterative gridding reconstruction method with correction of off-resonance artifacts was developed, which is especially tailored for multiple-shot non-Cartesian imaging. The novelty of the method lies in that the transformation matrix for gridding (T) was constructed as the convolution of two sparse matrices, among which the former is determined by the sampling interval and the spatial distribution of the off-resonance frequencies and the latter by the sampling trajectory and the target grid in the Cartesian space. The resulting T matrix is also sparse and can be solved efficiently with the iterative conjugate gradient algorithm. It was shown that, with the proposed method, the reconstruction speed in multiple-shot non-Cartesian imaging can be improved significantly while retaining high reconstruction fidelity. More important, the method proposed allows tradeoff between the accuracy and the computation time of reconstruction, making customization of the use of such a method in different applications possible. The performance of the proposed method was demonstrated by numerical simulation and multiple-shot spiral imaging on rat brain at 4.7 T. (c) 2010 Wiley-Liss, Inc.
Investigating of spatial variations of PM2.5 concentration in Suzhou using remote sensing imagery
NASA Astrophysics Data System (ADS)
Zhang, Shanzheng; Li, Bailiang
2017-04-01
Suzhou is located at the center of Yangtze Delta, suffering the air pollution from construction of mega city, industrial emission and traffic development. Particulate matter not greater than 2.5 micrometers (PM2.5) is now considered as the most important pollutants in the air in East China. For Suzhou city, some studies on PM2.5 temporal variations based on ground measurements have been conducted. However, until now, there is limited remote sensing based research to investigate the spatial pattern of PM2.5 in Suzhou. MODIS is often used to evaluate the spatial variabiilty of air quality, however, due to its low spatial resolution (250m), we have adopted China launched HJ-1 satellite with 30 m resolution of CCD sensor. Following the solar radiation S6 model and dark object atmospheric correction method (Kaufman,et al., 2000), atmospheric optical depth (AOD) was estimated. A statistical relationship has been built up between AOD and PM2.5. We have retrieved the spatial distribution of PM2.5 across Suzhou city in the winter of 2014. Results indicate that PM2.5 has the highest value in Kunshan (East of Suzhou) and Changshu and Taicang (NE of Suzhou) due to the heavy-polluted industry, while in the island of the Taihu Lake, the PM2.5 is significantly lower than other places maybe because of high deposition rate of PM2.5 over water and forest surfaces. The spatial variation also shows that traffic has less contribution to the PM2.5 generation than the industry. We believe this study will be very useful to identify the causes of local PM2.5 pollution. The findings could also benefit local management and policy making.
Kim, Kwanchul; Lee, Kwon H; Kim, Ji I; Noh, Youngmin; Shin, Dong H; Shin, Sung K; Lee, Dasom; Kim, Jhoon; Kim, Young J; Song, Chul H
2016-01-01
Surface-level PM10 distribution was estimated from the satellite aerosol optical depth (AOD) products, taking the account of vertical profiles and hygroscopicity of aerosols over Jeju, Korea during March 2008 and October 2009. In this study, MODIS AOD data from the Terra and Aqua satellites were corrected with aerosol extinction profiles and relative humidity data. PBLH (Planetary Boundary Layer Height) was determined from MPLNET lidar-derived aerosol extinction coefficient profiles. Through statistical analysis, better agreement in correlation (R = 0.82) between the hourly PM10 concentration and hourly average Sunphotometer AOD was the obtained when vertical fraction method (VFM) considering Haze Layer Height (HLH) and hygroscopic growth factor f(RH) was used. The validity of the derived relationship between satellite AOD and surface PM10 concentration clearly demonstrates that satellite AOD data can be utilized for remote sensing of spatial distribution of regional PM10 concentration. Copyright © 2015 The Authors. Published by Elsevier Ltd.. All rights reserved.
The Millimeter Sky Transparency Imager (MiSTI)
NASA Astrophysics Data System (ADS)
Tamura, Yoichi; Kawabe, Ryohei; Kohno, Kotaro; Fukuhara, Masayuki; Momose, Munetake; Ezawa, Hajime; Kuboi, Akihito; Sekiguchi, Tomohiko; Kamazaki, Takeshi; Vila-Vilaró, Baltasar; Nakagawa, Yuki; Okada, Norio
2011-04-01
The Millimeter Sky Transparency Imager (MiSTI) is a small millimeter-wave scanning telescope with a 25-cm diameter dish operating at 183 GHz. MiSTI is installed at Atacama, Chile, and it measures emission from atmospheric water vapor and its fluctuations to estimate atmospheric absorption in the millimeter to submillimeter range. MiSTI observes the water vapor distribution at a spatial resolution of 0.°5, and it is sensitive enough to detect an excess path length of lesssim0.05 mm for an integration time of 1 s. By comparing the MiSTI measurements with those by a 220 GHz tipper, we validated that the 183 GHz measurements of MiSTI are correct, down to the level of any residual systematic errors in the 220 GHz measurements. Since 2008, MiSTI has provided real-time (every 1 hr) monitoring of the all-sky opacity distribution and atmospheric transmission curves in the (sub)millimeter through the internet, allowing us to know the (sub)millimeter sky conditions at Atacama.
DOE Office of Scientific and Technical Information (OSTI.GOV)
Di, Zichao; Chen, Si; Hong, Young Pyo
X-ray fluorescence tomography is based on the detection of fluorescence x-ray photons produced following x-ray absorption while a specimen is rotated; it provides information on the 3D distribution of selected elements within a sample. One limitation in the quality of sample recovery is the separation of elemental signals due to the finite energy resolution of the detector. Another limitation is the effect of self-absorption, which can lead to inaccurate results with dense samples. To recover a higher quality elemental map, we combine x-ray fluorescence detection with a second data modality: conventional x-ray transmission tomography using absorption. By using these combinedmore » signals in a nonlinear optimization-based approach, we demonstrate the benefit of our algorithm on real experimental data and obtain an improved quantitative reconstruction of the spatial distribution of dominant elements in the sample. Furthermore, compared with single-modality inversion based on x-ray fluorescence alone, this joint inversion approach reduces ill-posedness and should result in improved elemental quantification and better correction of self-absorption.« less
Joint reconstruction of x-ray fluorescence and transmission tomography
Di, Zichao Wendy; Chen, Si; Hong, Young Pyo; Jacobsen, Chris; Leyffer, Sven; Wild, Stefan M.
2017-01-01
X-ray fluorescence tomography is based on the detection of fluorescence x-ray photons produced following x-ray absorption while a specimen is rotated; it provides information on the 3D distribution of selected elements within a sample. One limitation in the quality of sample recovery is the separation of elemental signals due to the finite energy resolution of the detector. Another limitation is the effect of self-absorption, which can lead to inaccurate results with dense samples. To recover a higher quality elemental map, we combine x-ray fluorescence detection with a second data modality: conventional x-ray transmission tomography using absorption. By using these combined signals in a nonlinear optimization-based approach, we demonstrate the benefit of our algorithm on real experimental data and obtain an improved quantitative reconstruction of the spatial distribution of dominant elements in the sample. Compared with single-modality inversion based on x-ray fluorescence alone, this joint inversion approach reduces ill-posedness and should result in improved elemental quantification and better correction of self-absorption. PMID:28788848
On the Computation of Sound by Large-Eddy Simulations
NASA Technical Reports Server (NTRS)
Piomelli, Ugo; Streett, Craig L.; Sarkar, Sutanu
1997-01-01
The effect of the small scales on the source term in Lighthill's acoustic analogy is investigated, with the objective of determining the accuracy of large-eddy simulations when applied to studies of flow-generated sound. The distribution of the turbulent quadrupole is predicted accurately, if models that take into account the trace of the SGS stresses are used. Its spatial distribution is also correct, indicating that the low-wave-number (or frequency) part of the sound spectrum can be predicted well by LES. Filtering, however, removes the small-scale fluctuations that contribute significantly to the higher derivatives in space and time of Lighthill's stress tensor T(sub ij). The rms fluctuations of the filtered derivatives are substantially lower than those of the unfiltered quantities. The small scales, however, are not strongly correlated, and are not expected to contribute significantly to the far-field sound; separate modeling of the subgrid-scale density fluctuations might, however, be required in some configurations.
Malyarenko, Dariya I; Pang, Yuxi; Senegas, Julien; Ivancevic, Marko K; Ross, Brian D; Chenevert, Thomas L
2015-12-01
Spatially non-uniform diffusion weighting bias due to gradient nonlinearity (GNL) causes substantial errors in apparent diffusion coefficient (ADC) maps for anatomical regions imaged distant from magnet isocenter. Our previously-described approach allowed effective removal of spatial ADC bias from three orthogonal DWI measurements for mono-exponential media of arbitrary anisotropy. The present work evaluates correction feasibility and performance for quantitative diffusion parameters of the two-component IVIM model for well-perfused and nearly isotropic renal tissue. Sagittal kidney DWI scans of a volunteer were performed on a clinical 3T MRI scanner near isocenter and offset superiorly. Spatially non-uniform diffusion weighting due to GNL resulted both in shift and broadening of perfusion-suppressed ADC histograms for off-center DWI relative to unbiased measurements close to isocenter. Direction-average DW-bias correctors were computed based on the known gradient design provided by vendor. The computed bias maps were empirically confirmed by coronal DWI measurements for an isotropic gel-flood phantom. Both phantom and renal tissue ADC bias for off-center measurements was effectively removed by applying pre-computed 3D correction maps. Comparable ADC accuracy was achieved for corrections of both b -maps and DWI intensities in presence of IVIM perfusion. No significant bias impact was observed for IVIM perfusion fraction.
Malyarenko, Dariya I.; Pang, Yuxi; Senegas, Julien; Ivancevic, Marko K.; Ross, Brian D.; Chenevert, Thomas L.
2015-01-01
Spatially non-uniform diffusion weighting bias due to gradient nonlinearity (GNL) causes substantial errors in apparent diffusion coefficient (ADC) maps for anatomical regions imaged distant from magnet isocenter. Our previously-described approach allowed effective removal of spatial ADC bias from three orthogonal DWI measurements for mono-exponential media of arbitrary anisotropy. The present work evaluates correction feasibility and performance for quantitative diffusion parameters of the two-component IVIM model for well-perfused and nearly isotropic renal tissue. Sagittal kidney DWI scans of a volunteer were performed on a clinical 3T MRI scanner near isocenter and offset superiorly. Spatially non-uniform diffusion weighting due to GNL resulted both in shift and broadening of perfusion-suppressed ADC histograms for off-center DWI relative to unbiased measurements close to isocenter. Direction-average DW-bias correctors were computed based on the known gradient design provided by vendor. The computed bias maps were empirically confirmed by coronal DWI measurements for an isotropic gel-flood phantom. Both phantom and renal tissue ADC bias for off-center measurements was effectively removed by applying pre-computed 3D correction maps. Comparable ADC accuracy was achieved for corrections of both b-maps and DWI intensities in presence of IVIM perfusion. No significant bias impact was observed for IVIM perfusion fraction. PMID:26811845
Imaging single atoms using secondary electrons with an aberration-corrected electron microscope.
Zhu, Y; Inada, H; Nakamura, K; Wall, J
2009-10-01
Aberration correction has embarked on a new frontier in electron microscopy by overcoming the limitations of conventional round lenses, providing sub-angstrom-sized probes. However, improvement of spatial resolution using aberration correction so far has been limited to the use of transmitted electrons both in scanning and stationary mode, with an improvement of 20-40% (refs 3-8). In contrast, advances in the spatial resolution of scanning electron microscopes (SEMs), which are by far the most widely used instrument for surface imaging at the micrometre-nanometre scale, have been stagnant, despite several recent efforts. Here, we report a new SEM, with aberration correction, able to image single atoms by detecting electrons emerging from its surface as a result of interaction with the small probe. The spatial resolution achieved represents a fourfold improvement over the best-reported resolution in any SEM (refs 10-12). Furthermore, we can simultaneously probe the sample through its entire thickness with transmitted electrons. This ability is significant because it permits the selective visualization of bulk atoms and surface ones, beyond a traditional two-dimensional projection in transmission electron microscopy. It has the potential to revolutionize the field of microscopy and imaging, thereby opening the door to a wide range of applications, especially when combined with simultaneous nanoprobe spectroscopy.
Extra-articular deformity correction using Taylor spatial frame prior to total knee arthroplasty.
Tawari, Gautam J K; Maheshwari, Rajan; Madan, Sanjeev S
2018-03-20
A good long-term outcome following a total knee arthroplasty relies on restoration of the mechanical axis and effective soft tissue balancing of the prosthetic knee. Arthroplasty surgery in patients with secondary osteoarthritis of the knee with an extra-articular tibial deformity is a complex and challenging procedure. The correction of mal-alignment of the mechanical axis is associated with unpredictable result and with higher revision rates. Single-staged deformity correction and replacement surgery often result in the use of constraint implants. We describe our experience with staged correction of deformity using a Taylor Spatial Frame (TSF) followed by total knee arthroplasty in these patients and highlight the advantage of staged approach. The use of TSF fixator for deformity correction prior to a primary total knee arthroplasty has not been described in the literature. We describe three cases of secondary osteoarthritis of the knee associated with multiplanar tibial deformity treated effectively with a total knee arthroplasty following deformity correction and union using a TSF. All patients had an improved Knee Society score and Oxford Knee score postoperatively and were satisfied with their replacement outcome. Staged deformity correction followed by arthroplasty allows the use of standard primary arthroplasty implants with predicable results and flexible aftercare. This approach may also provide significant improvement of patient symptoms following correction of deformity resulting in deferment of the arthroplasty surgery.
Exposure assessment in front of a multi-band base station antenna.
Kos, Bor; Valič, Blaž; Kotnik, Tadej; Gajšek, Peter
2011-04-01
This study investigates occupational exposure to electromagnetic fields in front of a multi-band base station antenna for mobile communications at 900, 1800, and 2100 MHz. Finite-difference time-domain method was used to first validate the antenna model against measurement results published in the literature and then investigate the specific absorption rate (SAR) in two heterogeneous, anatomically correct human models (Virtual Family male and female) at distances from 10 to 1000 mm. Special attention was given to simultaneous exposure to fields of three different frequencies, their interaction and the additivity of SAR resulting from each frequency. The results show that the highest frequency--2100 MHz--results in the highest spatial-peak SAR averaged over 10 g of tissue, while the whole-body SAR is similar at all three frequencies. At distances > 200 mm from the antenna, the whole-body SAR is a more limiting factor for compliance to exposure guidelines, while at shorter distances the spatial-peak SAR may be more limiting. For the evaluation of combined exposure, a simple summation of spatial-peak SAR maxima at each frequency gives a good estimation for combined exposure, which was also found to depend on the distribution of transmitting power between the different frequency bands. Copyright © 2010 Wiley-Liss, Inc.
A k-space method for acoustic propagation using coupled first-order equations in three dimensions.
Tillett, Jason C; Daoud, Mohammad I; Lacefield, James C; Waag, Robert C
2009-09-01
A previously described two-dimensional k-space method for large-scale calculation of acoustic wave propagation in tissues is extended to three dimensions. The three-dimensional method contains all of the two-dimensional method features that allow accurate and stable calculation of propagation. These features are spectral calculation of spatial derivatives, temporal correction that produces exact propagation in a homogeneous medium, staggered spatial and temporal grids, and a perfectly matched boundary layer. Spectral evaluation of spatial derivatives is accomplished using a fast Fourier transform in three dimensions. This computational bottleneck requires all-to-all communication; execution time in a parallel implementation is therefore sensitive to node interconnect latency and bandwidth. Accuracy of the three-dimensional method is evaluated through comparisons with exact solutions for media having spherical inhomogeneities. Large-scale calculations in three dimensions were performed by distributing the nearly 50 variables per voxel that are used to implement the method over a cluster of computers. Two computer clusters used to evaluate method accuracy are compared. Comparisons of k-space calculations with exact methods including absorption highlight the need to model accurately the medium dispersion relationships, especially in large-scale media. Accurately modeled media allow the k-space method to calculate acoustic propagation in tissues over hundreds of wavelengths.
NASA Astrophysics Data System (ADS)
Zhang, Yongqian; Brandner, Edward; Ozhasoglu, Cihat; Lalonde, Ron; Heron, Dwight E.; Saiful Huq, M.
2018-02-01
The use of small fields in radiation therapy techniques has increased substantially in particular in stereotactic radiosurgery (SRS) and stereotactic body radiation therapy (SBRT). However, as field size reduces further still, the response of the detector changes more rapidly with field size, and the effects of measurement uncertainties become increasingly significant due to the lack of lateral charged particle equilibrium, spectral changes as a function of field size, detector choice, and subsequent perturbations of the charged particle fluence. This work presents a novel 3D dose volume-to-point correction method to predict the readings of a 0.015 cc PinPoint chamber (PTW 31014) for both small static-fields and composite-field dosimetry formed by fixed cones on the CyberKnife® M6™ machine. A 3D correction matrix is introduced to link the 3D dose distribution to the response of the PinPoint chamber in water. The parameters of the correction matrix are determined by modeling its 3D dose response in circular fields created using the 12 fixed cones (5 mm-60 mm) on a CyberKnife® M6™ machine. A penalized least-square optimization problem is defined by fitting the calculated detector reading to the experimental measurement data to generate the optimal correction matrix; the simulated annealing algorithm is used to solve the inverse optimization problem. All the experimental measurements are acquired for every 2 mm chamber shift in the horizontal planes for each field size. The 3D dose distributions for the measurements are calculated using the Monte Carlo calculation with the MultiPlan® treatment planning system (Accuray Inc., Sunnyvale, CA, USA). The performance evaluation of the 3D conversion matrix is carried out by comparing the predictions of the output factors (OFs), off-axis ratios (OARs) and percentage depth dose (PDD) data to the experimental measurement data. The discrepancy of the measurement and the prediction data for composite fields is also performed for clinical SRS plans. The optimization algorithm used for generating the optimal correction factors is stable, and the resulting correction factors were smooth in the spatial domain. The measurement and prediction of OFs agree closely with percentage differences of less than 1.9% for all the 12 cones. The discrepancies between the prediction and the measurement PDD readings at 50 mm and 80 mm depth are 1.7% and 1.9%, respectively. The percentage differences of OARs between measurement and prediction data are less than 2% in the low dose gradient region, and 2%/1 mm discrepancies are observed within the high dose gradient regions. The differences between the measurement and prediction data for all the CyberKnife based SRS plans are less than 1%. These results demonstrate the existence and efficiency of the novel 3D correction method for small field dosimetry. The 3D correction matrix links the 3D dose distribution and the reading of the PinPoint chamber. The comparison between the predicted reading and the measurement data for static small fields (OFs, OARs and PDDs) yield discrepancies within 2% for low dose gradient regions and 2%/1 mm for high dose gradient regions; the discrepancies between the predicted and the measurement data are less than 1% for all the SRS plans. The 3D correction method provides an access to evaluate the clinical measurement data and can be applied to non-standard composite fields intensity modulated radiation therapy point dose verification.
Deterministic ion beam material adding technology for high-precision optical surfaces.
Liao, Wenlin; Dai, Yifan; Xie, Xuhui; Zhou, Lin
2013-02-20
Although ion beam figuring (IBF) provides a highly deterministic method for the precision figuring of optical components, several problems still need to be addressed, such as the limited correcting capability for mid-to-high spatial frequency surface errors and low machining efficiency for pit defects on surfaces. We propose a figuring method named deterministic ion beam material adding (IBA) technology to solve those problems in IBF. The current deterministic optical figuring mechanism, which is dedicated to removing local protuberances on optical surfaces, is enriched and developed by the IBA technology. Compared with IBF, this method can realize the uniform convergence of surface errors, where the particle transferring effect generated in the IBA process can effectively correct the mid-to-high spatial frequency errors. In addition, IBA can rapidly correct the pit defects on the surface and greatly improve the machining efficiency of the figuring process. The verification experiments are accomplished on our experimental installation to validate the feasibility of the IBA method. First, a fused silica sample with a rectangular pit defect is figured by using IBA. Through two iterations within only 47.5 min, this highly steep pit is effectively corrected, and the surface error is improved from the original 24.69 nm root mean square (RMS) to the final 3.68 nm RMS. Then another experiment is carried out to demonstrate the correcting capability of IBA for mid-to-high spatial frequency surface errors, and the final results indicate that the surface accuracy and surface quality can be simultaneously improved.
NASA Technical Reports Server (NTRS)
Pagnutti, Mary; Holekamp, Kara; Ryan, Robert E.; Vaughan, Ronand; Russell, Jeff; Prados, Don; Stanley, Thomas
2005-01-01
Remotely sensed ground reflectance is the foundation of any interoperability or change detection technique. Satellite intercomparisons and accurate vegetation indices, such as the Normalized Difference Vegetation Index (NDVI), require the generation of accurate reflectance maps (NDVI is used to describe or infer a wide variety of biophysical parameters and is defined in terms of near-infrared (NIR) and red band reflectances). Accurate reflectance-map generation from satellite imagery relies on the removal of solar and satellite geometry and of atmospheric effects and is generally referred to as atmospheric correction. Atmospheric correction of remotely sensed imagery to ground reflectance has been widely applied to a few systems only. The ability to obtain atmospherically corrected imagery and products from various satellites is essential to enable widescale use of remotely sensed, multitemporal imagery for a variety of applications. An atmospheric correction approach derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) that can be applied to high-spatial-resolution satellite imagery under many conditions was evaluated to demonstrate a reliable, effective reflectance map generation method. Additional information is included in the original extended abstract.
NASA Technical Reports Server (NTRS)
Pagnutti, Mary; Holekamp, Kara; Ryan, Robert E.; Vaughan, Ronald; Russell, Jeffrey A.; Prados, Don; Stanley, Thomas
2005-01-01
Remotely sensed ground reflectance is the basis for many inter-sensor interoperability or change detection techniques. Satellite inter-comparisons and accurate vegetation indices such as the Normalized Difference Vegetation Index, which is used to describe or to imply a wide variety of biophysical parameters and is defined in terms of near-infrared and redband reflectance, require the generation of accurate reflectance maps. This generation relies upon the removal of solar illumination, satellite geometry, and atmospheric effects and is generally referred to as atmospheric correction. Atmospheric correction of remotely sensed imagery to ground reflectance, however, has been widely applied to only a few systems. In this study, we atmospherically corrected commercially available, high spatial resolution IKONOS and QuickBird imagery using several methods to determine the accuracy of the resulting reflectance maps. We used extensive ground measurement datasets for nine IKONOS and QuickBird scenes acquired over a two-year period to establish reflectance map accuracies. A correction approach using atmospheric products derived from Moderate Resolution Imaging Spectrometer data created excellent reflectance maps and demonstrated a reliable, effective method for reflectance map generation.
Rijal, Jhalendra P; Wilson, Rob; Godfrey, Larry D
2016-02-01
Twospotted spider mite, Tetranychus urticae Koch, is an important pest of peppermint in California, USA. Spider mite feeding on peppermint leaves causes physiological changes in the plant, which coupling with the favorable environmental condition can lead to increased mite infestations. Significant yield loss can occur in absence of pest monitoring and timely management. Understating the within-field spatial distribution of T. urticae is critical for the development of reliable sampling plan. The study reported here aims to characterize the spatial distribution of mite infestation in four commercial peppermint fields in northern California using spatial techniques, variogram and Spatial Analysis by Distance IndicEs (SADIE). Variogram analysis revealed that there was a strong evidence for spatially dependent (aggregated) mite population in 13 of 17 sampling dates and the physical distance of the aggregation reached maximum to 7 m in peppermint fields. Using SADIE, 11 of 17 sampling dates showed aggregated distribution pattern of mite infestation. Combining results from variogram and SADIE analysis, the spatial aggregation of T. urticae was evident in all four fields for all 17 sampling dates evaluated. Comparing spatial association using SADIE, ca. 62% of the total sampling pairs showed a positive association of mite spatial distribution patterns between two consecutive sampling dates, which indicates a strong spatial and temporal stability of mite infestation in peppermint fields. These results are discussed in relation to behavior of spider mite distribution within field, and its implications for improving sampling guidelines that are essential for effective pest monitoring and management.
Thematic and spatial resolutions affect model-based predictions of tree species distribution.
Liang, Yu; He, Hong S; Fraser, Jacob S; Wu, ZhiWei
2013-01-01
Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution.
Thematic and Spatial Resolutions Affect Model-Based Predictions of Tree Species Distribution
Liang, Yu; He, Hong S.; Fraser, Jacob S.; Wu, ZhiWei
2013-01-01
Subjective decisions of thematic and spatial resolutions in characterizing environmental heterogeneity may affect the characterizations of spatial pattern and the simulation of occurrence and rate of ecological processes, and in turn, model-based tree species distribution. Thus, this study quantified the importance of thematic and spatial resolutions, and their interaction in predictions of tree species distribution (quantified by species abundance). We investigated how model-predicted species abundances changed and whether tree species with different ecological traits (e.g., seed dispersal distance, competitive capacity) had different responses to varying thematic and spatial resolutions. We used the LANDIS forest landscape model to predict tree species distribution at the landscape scale and designed a series of scenarios with different thematic (different numbers of land types) and spatial resolutions combinations, and then statistically examined the differences of species abundance among these scenarios. Results showed that both thematic and spatial resolutions affected model-based predictions of species distribution, but thematic resolution had a greater effect. Species ecological traits affected the predictions. For species with moderate dispersal distance and relatively abundant seed sources, predicted abundance increased as thematic resolution increased. However, for species with long seeding distance or high shade tolerance, thematic resolution had an inverse effect on predicted abundance. When seed sources and dispersal distance were not limiting, the predicted species abundance increased with spatial resolution and vice versa. Results from this study may provide insights into the choice of thematic and spatial resolutions for model-based predictions of tree species distribution. PMID:23861828
Insaf, Tabassum Z; Talbot, Thomas
2016-07-01
To assess the geographic distribution of Low Birth Weight (LBW) in New York State among singleton births using a spatial regression approach in order to identify priority areas for public health actions. LBW was defined as birth weight less than 2500g. Geocoded data from 562,586 birth certificates in New York State (years 2008-2012) were merged with 2010 census data at the tract level. To provide stable estimates and maintain confidentiality, data were aggregated to yield 1268 areas of analysis. LBW prevalence among singleton births was related with area-level behavioral, socioeconomic and demographic characteristics using a Poisson mixed effects spatial error regression model. Observed low birth weight showed statistically significant auto-correlation in our study area (Moran's I 0.16 p value 0.0005). After over-dispersion correction and accounting for fixed effects for selected social determinants, spatial autocorrelation was fully accounted for (Moran's I-0.007 p value 0.241). The proportion of LBW was higher in areas with larger Hispanic or Black populations and high smoking prevalence. Smoothed maps with predicted prevalence were developed to identify areas at high risk of LBW. Spatial patterns of residual variation were analyzed to identify unique risk factors. Neighborhood racial composition contributes to disparities in LBW prevalence beyond differences in behavioral and socioeconomic factors. Small-area analyses of LBW can identify areas for targeted interventions and display unique local patterns that should be accounted for in prevention strategies. Copyright © 2016 The Authors. Published by Elsevier Inc. All rights reserved.
An inverse approach to determining spatially varying arterial compliance using ultrasound imaging
NASA Astrophysics Data System (ADS)
Mcgarry, Matthew; Li, Ronny; Apostolakis, Iason; Nauleau, Pierre; Konofagou, Elisa E.
2016-08-01
The mechanical properties of arteries are implicated in a wide variety of cardiovascular diseases, many of which are expected to involve a strong spatial variation in properties that can be depicted by diagnostic imaging. A pulse wave inverse problem (PWIP) is presented, which can produce spatially resolved estimates of vessel compliance from ultrasound measurements of the vessel wall displacements. The 1D equations governing pulse wave propagation in a flexible tube are parameterized by the spatially varying properties, discrete cosine transform components of the inlet pressure boundary conditions, viscous loss constant and a resistance outlet boundary condition. Gradient descent optimization is used to fit displacements from the model to the measured data by updating the model parameters. Inversion of simulated data showed that the PWIP can accurately recover the correct compliance distribution and inlet pressure under realistic conditions, even under high simulated measurement noise conditions. Silicone phantoms with known compliance contrast were imaged with a clinical ultrasound system. The PWIP produced spatially and quantitatively accurate maps of the phantom compliance compared to independent static property estimates, and the known locations of stiff inclusions (which were as small as 7 mm). The PWIP is necessary for these phantom experiments as the spatiotemporal resolution, measurement noise and compliance contrast does not allow accurate tracking of the pulse wave velocity using traditional approaches (e.g. 50% upstroke markers). Results from simulations indicate reflections generated from material interfaces may negatively affect wave velocity estimates, whereas these reflections are accounted for in the PWIP and do not cause problems.
NASA Astrophysics Data System (ADS)
Boldina, Inna; Beninger, Peter G.
2014-04-01
Despite its ubiquity and its role as an ecosystem engineer on temperate intertidal mudflats, little is known of the spatial ecology of the lugworm Arenicola marina. We estimated lugworm densities and analyzed the spatial distribution of A. marina on a French Atlantic mudflat subjected to long-term clam digging activities, and compared these to a nearby pristine reference mudflat, using a combination of geostatistical techniques: point-pattern analysis, autocorrelation, and wavelet analysis. Lugworm densities were an order of magnitude greater at the reference site. Although A. marina showed an aggregative spatial distribution at both sites, the characteristics and intensity of aggregation differed markedly between sites. The reference site showed an inhibition process (regular distribution) at distances <7.5 cm, whereas the impacted site showed a random distribution at this scale. At distances from 15 cm to several tens of meters, the spatial distribution of A. marina was clearly aggregated at both sites; however, the autocorrelation strength was much weaker at the impacted site. In addition, the non-impacted site presented multi-scale spatial distribution, which was not evident at the impacted site. The differences observed between the spatial distributions of the fishing-impacted vs. the non-impacted site reflect similar findings for other components of these two mudflat ecosystems, suggesting common community-level responses to prolonged mechanical perturbation: a decrease in naturally-occurring aggregation. This change may have consequences for basic biological characteristics such as reproduction, recruitment, growth, and feeding.
NASA Astrophysics Data System (ADS)
Alvarez-Garreton, C.; Ryu, D.; Western, A. W.; Su, C.-H.; Crow, W. T.; Robertson, D. E.; Leahy, C.
2014-09-01
Assimilation of remotely sensed soil moisture data (SM-DA) to correct soil water stores of rainfall-runoff models has shown skill in improving streamflow prediction. In the case of large and sparsely monitored catchments, SM-DA is a particularly attractive tool. Within this context, we assimilate active and passive satellite soil moisture (SSM) retrievals using an ensemble Kalman filter to improve operational flood prediction within a large semi-arid catchment in Australia (>40 000 km2). We assess the importance of accounting for channel routing and the spatial distribution of forcing data by applying SM-DA to a lumped and a semi-distributed scheme of the probability distributed model (PDM). Our scheme also accounts for model error representation and seasonal biases and errors in the satellite data. Before assimilation, the semi-distributed model provided more accurate streamflow prediction (Nash-Sutcliffe efficiency, NS = 0.77) than the lumped model (NS = 0.67) at the catchment outlet. However, this did not ensure good performance at the "ungauged" inner catchments. After SM-DA, the streamflow ensemble prediction at the outlet was improved in both the lumped and the semi-distributed schemes: the root mean square error of the ensemble was reduced by 27 and 31%, respectively; the NS of the ensemble mean increased by 7 and 38%, respectively; the false alarm ratio was reduced by 15 and 25%, respectively; and the ensemble prediction spread was reduced while its reliability was maintained. Our findings imply that even when rainfall is the main driver of flooding in semi-arid catchments, adequately processed SSM can be used to reduce errors in the model soil moisture, which in turn provides better streamflow ensemble prediction. We demonstrate that SM-DA efficacy is enhanced when the spatial distribution in forcing data and routing processes are accounted for. At ungauged locations, SM-DA is effective at improving streamflow ensemble prediction, however, the updated prediction is still poor since SM-DA does not address systematic errors in the model.
A multistate dynamic site occupancy model for spatially aggregated sessile communities
Fukaya, Keiichi; Royle, J. Andrew; Okuda, Takehiro; Nakaoka, Masahiro; Noda, Takashi
2017-01-01
Estimation of transition probabilities of sessile communities seems easy in principle but may still be difficult in practice because resampling error (i.e. a failure to resample exactly the same location at fixed points) may cause significant estimation bias. Previous studies have developed novel analytical methods to correct for this estimation bias. However, they did not consider the local structure of community composition induced by the aggregated distribution of organisms that is typically observed in sessile assemblages and is very likely to affect observations.We developed a multistate dynamic site occupancy model to estimate transition probabilities that accounts for resampling errors associated with local community structure. The model applies a nonparametric multivariate kernel smoothing methodology to the latent occupancy component to estimate the local state composition near each observation point, which is assumed to determine the probability distribution of data conditional on the occurrence of resampling error.By using computer simulations, we confirmed that an observation process that depends on local community structure may bias inferences about transition probabilities. By applying the proposed model to a real data set of intertidal sessile communities, we also showed that estimates of transition probabilities and of the properties of community dynamics may differ considerably when spatial dependence is taken into account.Results suggest the importance of accounting for resampling error and local community structure for developing management plans that are based on Markovian models. Our approach provides a solution to this problem that is applicable to broad sessile communities. It can even accommodate an anisotropic spatial correlation of species composition, and may also serve as a basis for inferring complex nonlinear ecological dynamics.
NASA Astrophysics Data System (ADS)
Zhou, Zhengzheng; Smith, James A.; Yang, Long; Baeck, Mary Lynn; Chaney, Molly; Ten Veldhuis, Marie-Claire; Deng, Huiping; Liu, Shuguang
2017-08-01
We examine urban flood response through data-driven analyses for a diverse sample of "small" watersheds (basin scale ranging from 7.0 to 111.1 km2) in the Charlotte Metropolitan region. These watersheds have experienced extensive urbanization and suburban development since the 1960s. The objective of this study is to develop a broad characterization of land surface and hydrometeorological controls of urban flood hydrology. Our analyses are based on peaks-over-threshold flood data developed from USGS streamflow observations and are motivated by problems of flood hazard characterization for urban regions. We examine flood-producing rainfall using high-resolution (1 km2 spatial resolution and 15 min time resolution), bias-corrected radar rainfall fields that are developed through the Hydro-NEXRAD system. The analyses focus on the 2001-2015 period. The results highlight the complexities of urban flood response. There are striking spatial heterogeneities in flood peak magnitudes, response times, and runoff ratios across the study region. These spatial heterogeneities are mainly linked to watershed scale, the distribution of impervious cover, and storm water management. Contrasting land surface properties also determine the mixture of flood-generating mechanisms for a particular watershed. Warm-season thunderstorm systems and tropical cyclones are main flood agents in Charlotte, with winter/spring storms playing a role in less-urbanized watersheds. The mixture of flood agents exerts a strong impact on the upper tail of flood frequency distributions. Antecedent watershed wetness plays a minor role in urban flood response, compared with less-urbanized watersheds. Implications for flood hazard characterization in urban watersheds and for advances in flood science are discussed.
Scholl, A; Marcus, M A; Doran, A; Nasiatka, J R; Young, A T; MacDowell, A A; Streubel, R; Kent, N; Feng, J; Wan, W; Padmore, H A
2018-05-01
Aberration correction by an electron mirror dramatically improves the spatial resolution and transmission of photoemission electron microscopes. We will review the performance of the recently installed aberration corrector of the X-ray Photoemission Electron Microscope PEEM-3 and show a large improvement in the efficiency of the electron optics. Hartmann testing is introduced as a quantitative method to measure the geometrical aberrations of a cathode lens electron microscope. We find that aberration correction leads to an order of magnitude reduction of the spherical aberrations, suggesting that a spatial resolution of below 100 nm is possible at 100% transmission of the optics when using x-rays. We demonstrate this improved performance by imaging test patterns employing element and magnetic contrast. Published by Elsevier B.V.
NASA Technical Reports Server (NTRS)
Sharma, P. K.; Knuth, E. L.
1977-01-01
Spatial and energy distributions of helium atoms scattered from an anodized 1235-0 aluminum surface as well as the tangential and normal momentum accommodation coefficients calculated from these distributions are reported. A procedure for calculating drag coefficients from measured values of spatial and energy distributions is given. The drag coefficient calculated for a 6061 T-6 aluminum sphere is included.
Nolen, Matthew S.; Magoulick, Daniel D.; DiStefano, Robert J.; Imhoff, Emily M.; Wagner, Brian K.
2014-01-01
We found that a range of environmental variables were important in predicting crayfish distribution and abundance at multiple spatial scales and their importance was species-, response variable- and scale dependent. We would encourage others to examine the influence of spatial scale on species distribution and abundance patterns.
USDA-ARS?s Scientific Manuscript database
Thirty one years of spatially distributed air temperature, relative humidity, dew point temperature, precipitation amount, and precipitation phase data are presented for the Reynolds Creek Experimental Watershed. The data are spatially distributed over a 10m Lidar-derived digital elevation model at ...
Dongjiao Liu; Hao Jiang; Robin Zhang; Kate S. He
2011-01-01
The spatial distribution of most invasive plants is poorly documented and studied. This project examined and compared the spatial distribution of a successful invasive plant, Japanese honeysuckle (Lonicera japonica), in two similar-sized but ecologically distinct watersheds in western Kentucky (Ledbetter Creek) and western Tennessee (Panther Creek)....
NASA Astrophysics Data System (ADS)
Do, Tuan; Ghez, Andrea; Lu, Jessica R.; Morris, Mark R.; Yelda, Sylvana; Martinez, Gregory D.; Peter, Annika H. G.; Wright, Shelley; Bullock, James; Kaplinghat, Manoj; Matthews, K.
2012-07-01
We report on measurements of the luminosity function of early (young) and late-type (old) stars in the central 0.5 pc of the Milky Way nuclear star cluster as well as the density profiles of both components. The young (~ 6 Myr) and old stars (> 1 Gyr) in this region provide different physical probes of the environment around a supermassive black hole; the luminosity function of the young stars offers us a way to measure the initial mass function from star formation in an extreme environment, while the density profile of the old stars offers us a probe of the dynamical interaction of a star cluster with a massive black hole. The two stellar populations are separated through a near-infrared spectroscopic survey using the integral-field spectrograph OSIRIS on Keck II behind the laser guide star adaptive optics system. This spectroscopic survey is able to separate early-type (young) and late-type (old) stars with a completeness of 50% at K' = 15.5. We describe our method of completeness correction using a combination of star planting simulations and Bayesian inference. The completeness corrected luminosity function of the early-type stars contains significantly more young stars at faint magnitudes compared to previous surveys with similar depth. In addition, by using proper motion and radial velocity measurements along with anisotropic spherical Jeans modeling of the cluster, it is possible to measure the spatial density profile of the old stars, which has been difficult to constrain with number counts alone. The most probable model shows that the spatial density profile, n(r) propto r-γ, to be shallow with γ = 0.4 ± 0.2, which is much flatter than the dynamically relaxed case of γ = 3/2 to 7/4, but does rule out a 'hole' in the distribution of old stars. We show, for the first time, that the spatial density profile, the black hole mass, and velocity anisotropy can be fit simultaneously to obtain a black hole mass that is consistent with that derived from individual orbits of stars at distances < 1000 AU from the Galactic center.